Artificial hummingbird algorithm: A new bio-inspired optimizer with its engineering applications
A new bio-inspired optimization algorithm called artificial hummingbird algorithm (AHA) is proposed in this work to solve optimization problems. The AHA algorithm simulates the special flight skills and intelligent foraging strategies of hummingbirds in nature. Three kinds of flight skills utilized...
Gespeichert in:
| Veröffentlicht in: | Computer methods in applied mechanics and engineering Jg. 388; S. 114194 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Amsterdam
Elsevier B.V
01.01.2022
Elsevier BV |
| Schlagworte: | |
| ISSN: | 0045-7825, 1879-2138 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | A new bio-inspired optimization algorithm called artificial hummingbird algorithm (AHA) is proposed in this work to solve optimization problems. The AHA algorithm simulates the special flight skills and intelligent foraging strategies of hummingbirds in nature. Three kinds of flight skills utilized in foraging strategies, including axial, diagonal, and omnidirectional flights, are modeled. In addition, guided foraging, territorial foraging, and migrating foraging are implemented, and a visit table is constructed to model the memory function of hummingbirds for food sources. AHA is validated using two sets of numerical test functions, and the results are compared with those obtained from various algorithms. The comparisons demonstrate that AHA is more competitive than other meta-heuristic algorithms and determine high-quality solutions with fewer control parameters. Additionally, the performance of AHA is validated on ten challenging engineering design cases studies. The results show the superior effectiveness of AHA in terms of computational burden and solution precision compared with the existing optimization techniques in literature. The study also explores the application of AHA in hydropower operation design to further demonstrate its potential in practice. The source code of AHA is publicly available at https://seyedalimirjalili.com/aha and https://www.mathworks.com/matlabcentral/fileexchange/101133-artificial-hummingbird-algorithm?s_tid=srchtitle. |
|---|---|
| AbstractList | A new bio-inspired optimization algorithm called artificial hummingbird algorithm (AHA) is proposed in this work to solve optimization problems. The AHA algorithm simulates the special flight skills and intelligent foraging strategies of hummingbirds in nature. Three kinds of flight skills utilized in foraging strategies, including axial, diagonal, and omnidirectional flights, are modeled. In addition, guided foraging, territorial foraging, and migrating foraging are implemented, and a visit table is constructed to model the memory function of hummingbirds for food sources. AHA is validated using two sets of numerical test functions, and the results are compared with those obtained from various algorithms. The comparisons demonstrate that AHA is more competitive than other meta-heuristic algorithms and determine high-quality solutions with fewer control parameters. Additionally, the performance of AHA is validated on ten challenging engineering design cases studies. The results show the superior effectiveness of AHA in terms of computational burden and solution precision compared with the existing optimization techniques in literature. The study also explores the application of AHA in hydropower operation design to further demonstrate its potential in practice. The source code of AHA is publicly available at https://seyedalimirjalili.com/aha and https://www.mathworks.com/matlabcentral/fileexchange/101133-artificial-hummingbird-algorithm?s_tid=srchtitle. |
| ArticleNumber | 114194 |
| Author | Wang, Liying Zhao, Weiguo Mirjalili, Seyedali |
| Author_xml | – sequence: 1 givenname: Weiguo surname: Zhao fullname: Zhao, Weiguo email: zhaoweiguo@hebeu.edu.cn organization: School of Water Conservancy and Hydropower, Hebei University of Engineering, Handan, Hebei, 056038, China – sequence: 2 givenname: Liying orcidid: 0000-0001-6899-3289 surname: Wang fullname: Wang, Liying email: wangliying@hebeu.edu.cn organization: School of Water Conservancy and Hydropower, Hebei University of Engineering, Handan, Hebei, 056038, China – sequence: 3 givenname: Seyedali surname: Mirjalili fullname: Mirjalili, Seyedali email: ali.mirjalili@gmail.com organization: Centre for Artificial Intelligence Research and Optimisation, Torrens University Australia, Fortitude Valley, Brisbane, 4006, QLD, Australia |
| BookMark | eNp9kMFu1DAQhi1UJLaFB-BmiXMWjx2vHTitKgpIlbjA2TjOZDurxA62lwqenizLiUPnMpf_-0fzXbOrmCIy9hrEFgTs3h63YfZbKSRsAVro2mdsA9Z0jQRlr9hGiFY3xkr9gl2XchTrWJAb9n2fK40UyE_84TTPFA895YH76ZAy1Yf5Hd_ziI-8p9RQLAtlHHhaKs30GzN_XDOcauEYDxQR81rA_bJMFHylFMtL9nz0U8FX__YN-3b34evtp-b-y8fPt_v7JqidrU2vg7HB9LIPuu-ECr0USmvlDaqhRWhRKwWia8fBBB98ZwE6MwxCByVHY9UNe3PpXXL6ccJS3TGdclxPOrmT0oLS6pyCSyrkVErG0S2ZZp9_ORDuLNId3SrSnUW6i8iVMf8xgerf52r2ND1Jvr-QuD7-kzC7EghjwGG1GKobEj1B_wE-UJAR |
| CitedBy_id | crossref_primary_10_1016_j_cma_2025_118318 crossref_primary_10_1016_j_ins_2023_119766 crossref_primary_10_1038_s41598_022_27144_4 crossref_primary_10_1016_j_ijsrc_2024_08_002 crossref_primary_10_1007_s10586_024_04666_2 crossref_primary_10_1016_j_ins_2023_119889 crossref_primary_10_1038_s41598_025_86298_z crossref_primary_10_1016_j_asoc_2022_109845 crossref_primary_10_1016_j_asoc_2023_111090 crossref_primary_10_1016_j_jece_2024_112210 crossref_primary_10_1007_s42235_024_00493_8 crossref_primary_10_3390_pr13082433 crossref_primary_10_1007_s11831_023_09912_1 crossref_primary_10_1016_j_egyr_2025_04_061 crossref_primary_10_1049_esi2_12175 crossref_primary_10_1007_s10586_024_04982_7 crossref_primary_10_1177_14759217251329080 crossref_primary_10_1016_j_cma_2022_115676 crossref_primary_10_1007_s42235_024_00515_5 crossref_primary_10_1016_j_est_2023_106952 crossref_primary_10_1177_09544062221133766 crossref_primary_10_1016_j_measen_2023_100917 crossref_primary_10_1016_j_epsr_2023_109742 crossref_primary_10_1038_s41598_024_77115_0 crossref_primary_10_1007_s42235_025_00653_4 crossref_primary_10_3390_a18040199 crossref_primary_10_1016_j_measurement_2024_115302 crossref_primary_10_1038_s41598_023_50959_8 crossref_primary_10_1016_j_eswa_2025_127945 crossref_primary_10_1016_j_est_2025_117069 crossref_primary_10_1016_j_ins_2022_07_131 crossref_primary_10_1016_j_jocs_2023_102152 crossref_primary_10_1007_s10462_024_11049_x crossref_primary_10_1016_j_enconman_2022_116523 crossref_primary_10_3390_app12199710 crossref_primary_10_1016_j_enconman_2025_119976 crossref_primary_10_3390_automation6020013 crossref_primary_10_1016_j_eswa_2023_120518 crossref_primary_10_1007_s11831_023_09900_5 crossref_primary_10_1007_s40009_025_01727_x crossref_primary_10_12677_MOS_2024_132095 crossref_primary_10_2166_hydro_2023_187 crossref_primary_10_1016_j_eswa_2024_123160 crossref_primary_10_1007_s41660_023_00369_0 crossref_primary_10_3390_math12152300 crossref_primary_10_1016_j_cma_2022_115223 crossref_primary_10_3390_biomimetics8060468 crossref_primary_10_1007_s10586_025_05528_1 crossref_primary_10_1088_1361_6501_acd713 crossref_primary_10_1007_s40435_025_01597_7 crossref_primary_10_1080_15440478_2022_2163026 crossref_primary_10_1002_jemt_24787 crossref_primary_10_3390_electronics10232975 crossref_primary_10_1002_cpe_7809 crossref_primary_10_1109_ACCESS_2022_3174222 crossref_primary_10_3390_biomimetics10040232 crossref_primary_10_1016_j_enconman_2023_116809 crossref_primary_10_1016_j_suscom_2023_100949 crossref_primary_10_1038_s41598_024_68239_4 crossref_primary_10_1371_journal_pone_0271692 crossref_primary_10_3390_fractalfract7090690 crossref_primary_10_3390_automation6030040 crossref_primary_10_1016_j_rico_2025_100543 crossref_primary_10_1016_j_swevo_2023_101378 crossref_primary_10_1108_EC_10_2024_0904 crossref_primary_10_1002_dac_5748 crossref_primary_10_1016_j_advengsoft_2022_103399 crossref_primary_10_1016_j_cie_2023_109212 crossref_primary_10_1088_1402_4896_ad86f7 crossref_primary_10_1007_s11227_024_06475_1 crossref_primary_10_3390_electronics12041058 crossref_primary_10_1007_s00170_025_15681_x crossref_primary_10_1016_j_oceaneng_2025_120701 crossref_primary_10_1038_s41598_024_54733_2 crossref_primary_10_1111_exsy_13683 crossref_primary_10_3390_pr12030490 crossref_primary_10_1007_s11581_025_06284_3 crossref_primary_10_1016_j_apenergy_2023_121007 crossref_primary_10_1016_j_engappai_2023_106121 crossref_primary_10_3390_biomimetics8020191 crossref_primary_10_1016_j_energy_2025_136671 crossref_primary_10_1016_j_advengsoft_2022_103158 crossref_primary_10_3390_app15105456 crossref_primary_10_1016_j_cie_2023_109765 crossref_primary_10_1016_j_compind_2025_104318 crossref_primary_10_4218_etrij_2023_0330 crossref_primary_10_1016_j_knosys_2023_110858 crossref_primary_10_3390_biomimetics10090629 crossref_primary_10_1007_s42235_023_00478_z crossref_primary_10_1016_j_apor_2024_104149 crossref_primary_10_1002_we_2908 crossref_primary_10_3390_drones7070452 crossref_primary_10_3233_JIFS_213206 crossref_primary_10_3390_sym14051021 crossref_primary_10_1049_gtd2_12900 crossref_primary_10_3390_math10132329 crossref_primary_10_47134_ppm_v2i2_1480 crossref_primary_10_1016_j_est_2023_109189 crossref_primary_10_1016_j_geoen_2023_211837 crossref_primary_10_1016_j_cma_2023_115878 crossref_primary_10_3390_su152014821 crossref_primary_10_1016_j_engappai_2022_105082 crossref_primary_10_3390_en15196966 crossref_primary_10_2166_wp_2023_050 crossref_primary_10_1016_j_cma_2024_117251 crossref_primary_10_1016_j_cma_2025_117791 crossref_primary_10_1016_j_est_2023_110288 crossref_primary_10_1016_j_eswa_2022_119021 crossref_primary_10_1007_s41939_024_00651_9 crossref_primary_10_1038_s41598_024_61453_0 crossref_primary_10_1016_j_neucom_2025_129816 crossref_primary_10_1038_s41598_023_48479_6 crossref_primary_10_1080_17517575_2025_2453244 crossref_primary_10_1038_s41598_025_13215_9 crossref_primary_10_1080_21642583_2024_2385310 crossref_primary_10_3390_fractalfract9080521 crossref_primary_10_1007_s10586_025_05613_5 crossref_primary_10_1007_s00521_024_10301_3 crossref_primary_10_1093_ce_zkad066 crossref_primary_10_1007_s44174_025_00453_8 crossref_primary_10_1177_09596518241247861 crossref_primary_10_3390_su152014831 crossref_primary_10_1007_s13198_024_02605_3 crossref_primary_10_1016_j_eswa_2022_119015 crossref_primary_10_1007_s10586_025_05113_6 crossref_primary_10_1016_j_energy_2024_130913 crossref_primary_10_1007_s42979_024_03290_6 crossref_primary_10_1016_j_aei_2022_101761 crossref_primary_10_32604_cmc_2023_041973 crossref_primary_10_1016_j_est_2023_109088 crossref_primary_10_1016_j_asoc_2024_111427 crossref_primary_10_1177_01436244241274924 crossref_primary_10_1080_0954898X_2024_2346115 crossref_primary_10_1016_j_ijhydene_2025_05_329 crossref_primary_10_1038_s41598_024_65292_x crossref_primary_10_1016_j_ijmecsci_2024_109589 crossref_primary_10_3390_electronics12071564 crossref_primary_10_1080_15567036_2023_2245771 crossref_primary_10_1016_j_rser_2025_115806 crossref_primary_10_1177_09544062241292935 crossref_primary_10_1016_j_jocs_2023_102010 crossref_primary_10_1016_j_apenergy_2024_124050 crossref_primary_10_1109_ACCESS_2023_3347587 crossref_primary_10_1007_s13042_024_02146_y crossref_primary_10_1088_1742_6596_2784_1_012017 crossref_primary_10_1016_j_swevo_2024_101807 crossref_primary_10_32604_cmes_2023_025908 crossref_primary_10_1016_j_applthermaleng_2024_124446 crossref_primary_10_1016_j_apenergy_2023_122015 crossref_primary_10_1186_s44147_024_00475_x crossref_primary_10_1016_j_eswa_2023_121744 crossref_primary_10_1038_s41598_022_24122_8 crossref_primary_10_1007_s00521_024_10346_4 crossref_primary_10_1109_ACCESS_2023_3241279 crossref_primary_10_1371_journal_pone_0317224 crossref_primary_10_1109_ACCESS_2023_3303328 crossref_primary_10_1016_j_measurement_2025_116769 crossref_primary_10_1155_2024_5568922 crossref_primary_10_1007_s10462_025_11351_2 crossref_primary_10_1016_j_cma_2023_116097 crossref_primary_10_1016_j_jocs_2024_102267 crossref_primary_10_1038_s41598_025_89089_8 crossref_primary_10_1109_ACCESS_2022_3195892 crossref_primary_10_1038_s41598_024_65182_2 crossref_primary_10_3390_biomimetics8020141 crossref_primary_10_1108_EC_03_2025_0205 crossref_primary_10_1016_j_energy_2025_138102 crossref_primary_10_1016_j_ins_2024_121054 crossref_primary_10_1080_23302674_2022_2070296 crossref_primary_10_1007_s00202_024_02720_1 crossref_primary_10_1002_dac_70162 crossref_primary_10_1109_ACCESS_2022_3172789 crossref_primary_10_1007_s10845_025_02655_9 crossref_primary_10_1016_j_measurement_2024_114191 crossref_primary_10_1007_s00170_024_14540_5 crossref_primary_10_1016_j_est_2022_104535 crossref_primary_10_1016_j_engappai_2023_106778 crossref_primary_10_1007_s42979_023_02356_1 crossref_primary_10_1109_ACCESS_2024_3397402 crossref_primary_10_1002_oca_3284 crossref_primary_10_1016_j_measurement_2025_117984 crossref_primary_10_1007_s42452_025_07578_x crossref_primary_10_3390_lubricants10110277 crossref_primary_10_3390_en17163962 crossref_primary_10_1007_s10278_022_00707_7 crossref_primary_10_1007_s10825_022_01921_w crossref_primary_10_1016_j_apm_2022_02_003 crossref_primary_10_3390_a17090417 crossref_primary_10_1007_s11227_024_06291_7 crossref_primary_10_3390_app14188280 crossref_primary_10_1177_30504554251319447 crossref_primary_10_3390_electronics14030403 crossref_primary_10_1016_j_cma_2022_114616 crossref_primary_10_1371_journal_pone_0325310 crossref_primary_10_1016_j_matcom_2022_01_010 crossref_primary_10_1007_s11227_022_04869_7 crossref_primary_10_1063_5_0225204 crossref_primary_10_1016_j_est_2025_117112 crossref_primary_10_1080_19942060_2024_2443128 crossref_primary_10_3390_s23146614 crossref_primary_10_1016_j_psep_2022_10_071 crossref_primary_10_1038_s41598_024_54910_3 crossref_primary_10_1038_s41598_025_94891_5 crossref_primary_10_1080_00051144_2023_2295142 crossref_primary_10_3390_biomimetics8020243 crossref_primary_10_1016_j_eswa_2023_121898 crossref_primary_10_1155_2024_7616065 crossref_primary_10_1007_s00158_022_03414_7 crossref_primary_10_1007_s11227_023_05790_3 crossref_primary_10_1016_j_cma_2022_115734 crossref_primary_10_1038_s41598_024_65867_8 crossref_primary_10_1016_j_eswa_2024_126185 crossref_primary_10_1007_s41024_024_00478_4 crossref_primary_10_1007_s00202_023_02098_6 crossref_primary_10_1016_j_energy_2022_124901 crossref_primary_10_1016_j_jreng_2024_05_001 crossref_primary_10_1007_s10462_024_10981_2 crossref_primary_10_1007_s42417_022_00819_y crossref_primary_10_1007_s00170_023_12205_3 crossref_primary_10_3390_math10081266 crossref_primary_10_1016_j_eswa_2022_119162 crossref_primary_10_1016_j_eswa_2025_129505 crossref_primary_10_1016_j_epsr_2025_111428 crossref_primary_10_1109_ACCESS_2023_3328248 crossref_primary_10_1177_13272314241295966 crossref_primary_10_1016_j_sca_2023_100039 crossref_primary_10_1515_cppm_2024_0011 crossref_primary_10_1371_journal_pone_0291788 crossref_primary_10_1038_s41598_023_38778_3 crossref_primary_10_1109_ACCESS_2025_3575496 crossref_primary_10_1007_s12065_024_00945_4 crossref_primary_10_1016_j_knosys_2025_113145 crossref_primary_10_1016_j_compbiomed_2022_106404 crossref_primary_10_3390_math10152675 crossref_primary_10_1080_01969722_2024_2343988 crossref_primary_10_1016_j_rineng_2025_104840 crossref_primary_10_1016_j_apm_2023_12_014 crossref_primary_10_1007_s00500_023_08274_x crossref_primary_10_3390_en17153830 crossref_primary_10_1016_j_energy_2023_127083 crossref_primary_10_1016_j_apenergy_2022_119605 crossref_primary_10_3390_app122211829 crossref_primary_10_1007_s10586_024_05024_y crossref_primary_10_1088_2057_1976_ad8c46 crossref_primary_10_1016_j_jallcom_2025_183847 crossref_primary_10_1038_s41598_024_79135_2 crossref_primary_10_1016_j_enconman_2023_116712 crossref_primary_10_1016_j_knosys_2022_109189 crossref_primary_10_1016_j_matcom_2022_02_030 crossref_primary_10_1016_j_procs_2024_04_173 crossref_primary_10_1007_s42947_025_00590_9 crossref_primary_10_1080_13682199_2023_2178611 crossref_primary_10_1016_j_knosys_2023_110587 crossref_primary_10_1016_j_egyr_2025_02_018 crossref_primary_10_1088_1361_6501_ad1807 crossref_primary_10_3390_biomimetics7040144 crossref_primary_10_1016_j_eswa_2023_122200 crossref_primary_10_32604_cmc_2024_046606 crossref_primary_10_2339_politeknik_1687239 crossref_primary_10_3390_en17246411 crossref_primary_10_3390_biomimetics10050343 crossref_primary_10_3390_math12111708 crossref_primary_10_1007_s00521_024_09928_z crossref_primary_10_1016_j_compbiomed_2023_106966 crossref_primary_10_1016_j_compag_2025_110573 crossref_primary_10_1038_s41598_025_90867_7 crossref_primary_10_1016_j_iot_2023_101010 crossref_primary_10_1007_s10586_024_04669_z crossref_primary_10_1007_s11042_023_16882_w crossref_primary_10_1007_s13755_023_00224_z crossref_primary_10_1016_j_knosys_2023_110454 crossref_primary_10_3390_ma18102366 crossref_primary_10_1088_1742_6596_2998_1_012008 crossref_primary_10_3390_math13111803 crossref_primary_10_3390_electronics11030318 crossref_primary_10_1109_ACCESS_2022_3198987 crossref_primary_10_1007_s41939_023_00252_y crossref_primary_10_1016_j_jocs_2025_102686 crossref_primary_10_1007_s10462_023_10403_9 crossref_primary_10_3233_JIFS_235607 crossref_primary_10_1016_j_egyr_2024_09_020 crossref_primary_10_1016_j_swevo_2024_101779 crossref_primary_10_1016_j_phycom_2022_101921 crossref_primary_10_1007_s00500_023_08033_y crossref_primary_10_1016_j_est_2023_108276 crossref_primary_10_3390_biomimetics8040377 crossref_primary_10_3390_math10163006 crossref_primary_10_1371_journal_pone_0297284 crossref_primary_10_1016_j_est_2024_115082 crossref_primary_10_1109_ACCESS_2024_3436899 crossref_primary_10_1038_s41598_024_60821_0 crossref_primary_10_1515_mt_2022_0123 crossref_primary_10_1007_s11042_025_20665_w crossref_primary_10_1016_j_advengsoft_2024_103671 crossref_primary_10_1016_j_knosys_2022_110248 crossref_primary_10_1016_j_knosys_2023_110305 crossref_primary_10_1186_s40537_025_01129_2 crossref_primary_10_1016_j_cie_2023_109815 crossref_primary_10_1080_0305215X_2024_2365712 crossref_primary_10_1007_s42835_024_01900_0 crossref_primary_10_1016_j_engappai_2023_106959 crossref_primary_10_1007_s11831_023_10030_1 crossref_primary_10_1016_j_prime_2025_101046 crossref_primary_10_1016_j_egyr_2025_02_043 crossref_primary_10_1002_oca_70013 crossref_primary_10_1080_02286203_2023_2240564 crossref_primary_10_1007_s10462_024_10919_8 crossref_primary_10_1007_s42044_025_00317_w crossref_primary_10_1016_j_knosys_2022_110011 crossref_primary_10_3390_machines10080602 crossref_primary_10_1007_s00521_024_10694_1 crossref_primary_10_1016_j_matcom_2023_10_021 crossref_primary_10_1016_j_ijepes_2023_109251 crossref_primary_10_1063_5_0096497 crossref_primary_10_1038_s41598_024_78086_y crossref_primary_10_56748_ejse_24791 crossref_primary_10_1016_j_est_2025_117733 crossref_primary_10_1038_s41598_023_39509_4 crossref_primary_10_1049_rpg2_12926 crossref_primary_10_1007_s11831_022_09800_0 crossref_primary_10_1007_s13198_025_02956_5 crossref_primary_10_1016_j_compbiomed_2022_106239 crossref_primary_10_1007_s10462_025_11269_9 crossref_primary_10_1016_j_rineng_2025_105984 crossref_primary_10_3390_app13095612 crossref_primary_10_1007_s40430_025_05404_4 crossref_primary_10_1007_s00500_023_08205_w crossref_primary_10_1007_s11709_024_1062_6 crossref_primary_10_1109_ACCESS_2023_3319452 crossref_primary_10_1016_j_eswa_2023_120188 crossref_primary_10_3390_math11163496 crossref_primary_10_3390_math12172604 crossref_primary_10_1038_s41598_024_83589_9 crossref_primary_10_3390_e25091277 crossref_primary_10_1016_j_cma_2022_114901 crossref_primary_10_1109_ACCESS_2022_3223388 crossref_primary_10_3390_su142416378 crossref_primary_10_1002_cpe_8306 crossref_primary_10_1007_s10586_025_05204_4 crossref_primary_10_3390_pr10122703 crossref_primary_10_1108_ECAM_05_2024_0676 crossref_primary_10_1080_15325008_2023_2283843 crossref_primary_10_1016_j_renene_2024_120011 crossref_primary_10_1002_ett_70128 crossref_primary_10_1016_j_jnca_2025_104217 crossref_primary_10_1049_rpg2_12817 crossref_primary_10_1007_s11227_024_05930_3 crossref_primary_10_1038_s41598_023_37537_8 crossref_primary_10_1016_j_egyr_2022_08_254 crossref_primary_10_1080_0952813X_2025_2515578 crossref_primary_10_1007_s00500_023_08630_x crossref_primary_10_1007_s11042_023_17570_5 crossref_primary_10_3390_rs15245789 crossref_primary_10_1016_j_est_2024_113090 crossref_primary_10_1016_j_istruc_2023_02_049 crossref_primary_10_1007_s40435_023_01172_y crossref_primary_10_1016_j_egyr_2022_09_025 crossref_primary_10_3390_math11040979 crossref_primary_10_1007_s00521_024_09769_w crossref_primary_10_3390_biomimetics10070445 crossref_primary_10_3390_math13010036 crossref_primary_10_1109_ACCESS_2022_3214206 crossref_primary_10_1016_j_heliyon_2024_e27244 crossref_primary_10_1016_j_ijhydene_2024_09_027 crossref_primary_10_1016_j_cma_2024_117718 crossref_primary_10_1016_j_knosys_2024_111850 crossref_primary_10_1016_j_asoc_2024_111905 crossref_primary_10_1038_s41598_024_54326_z crossref_primary_10_1063_5_0108340 crossref_primary_10_1038_s41598_024_81168_6 crossref_primary_10_1016_j_est_2025_115581 crossref_primary_10_3390_math13091389 crossref_primary_10_1016_j_oceaneng_2023_116663 crossref_primary_10_1007_s12065_024_00998_5 crossref_primary_10_3390_en15041302 crossref_primary_10_1016_j_jhydrol_2025_132998 crossref_primary_10_1038_s41598_025_99837_5 crossref_primary_10_1007_s10668_023_03712_0 crossref_primary_10_1007_s11042_024_19550_9 crossref_primary_10_1007_s11227_025_07596_x crossref_primary_10_3390_biomimetics9010020 crossref_primary_10_3390_s22051795 crossref_primary_10_1016_j_oceaneng_2024_117806 crossref_primary_10_1016_j_omega_2024_103034 crossref_primary_10_56748_ejse_24756 crossref_primary_10_1007_s11227_023_05227_x crossref_primary_10_1007_s12083_024_01675_1 crossref_primary_10_1016_j_energy_2024_130492 crossref_primary_10_3390_biom13071090 crossref_primary_10_1016_j_cscm_2025_e05167 crossref_primary_10_1002_ett_70037 crossref_primary_10_1007_s10489_023_04761_8 crossref_primary_10_1016_j_cosrev_2025_100727 crossref_primary_10_1016_j_cie_2022_108719 crossref_primary_10_1016_j_ijepes_2024_109849 crossref_primary_10_1016_j_engappai_2024_109202 crossref_primary_10_3389_fenrg_2022_905788 crossref_primary_10_1007_s12597_024_00785_x crossref_primary_10_1016_j_chaos_2024_114869 crossref_primary_10_1016_j_energy_2023_126705 crossref_primary_10_1049_rpg2_12855 crossref_primary_10_1016_j_cma_2024_116964 crossref_primary_10_55525_tjst_1214897 crossref_primary_10_1007_s11227_025_07234_6 crossref_primary_10_1109_ACCESS_2025_3546986 crossref_primary_10_1016_j_engstruct_2025_121261 crossref_primary_10_1007_s12065_024_00997_6 crossref_primary_10_1016_j_cma_2023_116062 crossref_primary_10_1109_TGRS_2024_3462752 crossref_primary_10_1007_s10462_025_11289_5 crossref_primary_10_1016_j_adhoc_2025_103836 crossref_primary_10_1007_s11042_022_11952_x crossref_primary_10_3390_app12178392 crossref_primary_10_3390_pr11020498 crossref_primary_10_3390_su15086358 crossref_primary_10_1007_s00521_022_07854_6 crossref_primary_10_3390_jmse12091676 crossref_primary_10_1038_s41598_024_72706_3 crossref_primary_10_1109_ACCESS_2022_3167395 crossref_primary_10_1007_s42107_024_01082_0 crossref_primary_10_1002_oca_3313 crossref_primary_10_1016_j_asoc_2024_112085 crossref_primary_10_1007_s41939_023_00330_1 crossref_primary_10_1007_s40009_025_01753_9 crossref_primary_10_1016_j_est_2025_115655 crossref_primary_10_1109_ACCESS_2023_3290895 crossref_primary_10_1007_s42235_024_00579_3 crossref_primary_10_1002_ese3_1628 crossref_primary_10_3390_a16090413 crossref_primary_10_1016_j_energ_2025_100016 crossref_primary_10_1038_s41598_024_75923_y crossref_primary_10_1016_j_eswa_2023_122147 crossref_primary_10_1016_j_knosys_2023_111257 crossref_primary_10_1016_j_bspc_2024_106485 crossref_primary_10_1016_j_eswa_2024_123428 crossref_primary_10_3390_drones8120749 crossref_primary_10_1016_j_egyr_2023_12_053 crossref_primary_10_1016_j_energy_2024_132766 crossref_primary_10_1007_s10586_024_04713_y crossref_primary_10_1016_j_heliyon_2024_e29339 crossref_primary_10_1016_j_compeleceng_2024_109407 crossref_primary_10_1016_j_aei_2023_102004 crossref_primary_10_1016_j_apenergy_2024_124853 crossref_primary_10_1007_s10462_025_11279_7 crossref_primary_10_1007_s10586_025_05427_5 crossref_primary_10_3390_su15032552 crossref_primary_10_3390_fi16100355 crossref_primary_10_1002_rnc_7894 crossref_primary_10_3390_sym16060708 crossref_primary_10_1016_j_cma_2024_117588 crossref_primary_10_3390_eng6080174 crossref_primary_10_1016_j_dajour_2022_100125 crossref_primary_10_1016_j_ijhydene_2024_09_211 crossref_primary_10_3390_pr10051014 crossref_primary_10_1016_j_rser_2025_115896 crossref_primary_10_1371_journal_pone_0328005 crossref_primary_10_1016_j_bspc_2024_106605 crossref_primary_10_1016_j_rineng_2025_104014 crossref_primary_10_3390_sym14112389 crossref_primary_10_1109_ACCESS_2022_3228782 crossref_primary_10_1002_eng2_12883 crossref_primary_10_1016_j_matcom_2022_12_001 crossref_primary_10_1080_23302674_2025_2465602 crossref_primary_10_1016_j_compstruct_2025_119227 crossref_primary_10_1016_j_seta_2023_103025 crossref_primary_10_1016_j_engappai_2022_104854 crossref_primary_10_1016_j_ress_2024_110092 crossref_primary_10_1186_s40537_023_00864_8 crossref_primary_10_1016_j_prime_2024_100474 crossref_primary_10_1016_j_suscom_2022_100821 crossref_primary_10_1007_s12145_025_01817_w crossref_primary_10_1080_0305215X_2025_2501647 crossref_primary_10_1177_14759217241233733 crossref_primary_10_1016_j_asoc_2025_113439 crossref_primary_10_3390_su152416707 crossref_primary_10_3390_app132212429 crossref_primary_10_1016_j_neucom_2025_130325 crossref_primary_10_1007_s10462_024_11104_7 crossref_primary_10_1007_s10489_023_04519_2 crossref_primary_10_1002_ett_4622 crossref_primary_10_1049_rpg2_13074 crossref_primary_10_1016_j_jece_2025_118339 crossref_primary_10_3390_app13053273 crossref_primary_10_1016_j_saa_2024_125205 crossref_primary_10_3390_math11081928 crossref_primary_10_1088_1748_3190_ae0080 crossref_primary_10_1007_s10586_024_05064_4 crossref_primary_10_19053_uptc_01211129_v34_n71_2025_18244 crossref_primary_10_1016_j_engappai_2022_104722 crossref_primary_10_1002_widm_1548 crossref_primary_10_1007_s10462_024_11029_1 crossref_primary_10_1016_j_asoc_2025_113527 crossref_primary_10_3390_en16041782 crossref_primary_10_1007_s11831_024_10135_1 crossref_primary_10_3390_w15030486 crossref_primary_10_1007_s12597_023_00721_5 crossref_primary_10_1007_s41870_024_01791_4 crossref_primary_10_1371_journal_pone_0311831 crossref_primary_10_1016_j_cma_2023_116200 crossref_primary_10_1007_s12065_023_00861_z crossref_primary_10_1016_j_ins_2024_120627 crossref_primary_10_1093_jcde_qwad094 crossref_primary_10_1016_j_ress_2024_110076 crossref_primary_10_1016_j_cie_2024_110103 crossref_primary_10_1016_j_cma_2023_116446 crossref_primary_10_1016_j_eswa_2023_122070 crossref_primary_10_1007_s12652_023_04569_x crossref_primary_10_1016_j_prime_2024_100494 crossref_primary_10_1007_s13198_025_02721_8 crossref_primary_10_1088_1742_6596_2339_1_012020 crossref_primary_10_1177_00219983231171690 crossref_primary_10_1109_ACCESS_2025_3552831 crossref_primary_10_1016_j_rineng_2025_104287 crossref_primary_10_1080_15435075_2025_2523508 crossref_primary_10_1016_j_compstruc_2023_107255 crossref_primary_10_1007_s00521_024_10764_4 crossref_primary_10_1007_s00202_024_02849_z crossref_primary_10_1109_ACCESS_2024_3361936 crossref_primary_10_1016_j_ecmx_2025_101019 crossref_primary_10_1109_ACCESS_2023_3295242 crossref_primary_10_1007_s00500_023_08577_z crossref_primary_10_1088_1402_4896_ad8e0e crossref_primary_10_55525_tjst_1160814 crossref_primary_10_1016_j_apenergy_2022_120031 crossref_primary_10_1080_09544828_2023_2180985 crossref_primary_10_1007_s11235_024_01225_3 crossref_primary_10_1007_s11276_025_03937_z crossref_primary_10_1016_j_swevo_2025_102009 crossref_primary_10_3390_en15239250 crossref_primary_10_1109_ACCESS_2023_3265712 crossref_primary_10_1080_19942060_2022_2098826 crossref_primary_10_1088_1361_6501_ad73f3 crossref_primary_10_1007_s10878_024_01189_9 crossref_primary_10_1093_jcde_qwae055 crossref_primary_10_3390_systems11080383 crossref_primary_10_1016_j_cma_2023_116582 crossref_primary_10_1007_s00521_024_10621_4 crossref_primary_10_1016_j_cma_2024_117411 crossref_primary_10_1016_j_knosys_2022_109615 crossref_primary_10_3390_machines12100721 crossref_primary_10_1007_s00202_024_02708_x crossref_primary_10_1016_j_asoc_2024_112371 crossref_primary_10_1016_j_renene_2024_120211 crossref_primary_10_1016_j_rineng_2025_104215 crossref_primary_10_1016_j_ijepes_2023_109719 crossref_primary_10_1063_5_0228020 crossref_primary_10_1007_s13748_024_00337_w crossref_primary_10_1016_j_tsep_2023_102178 crossref_primary_10_1016_j_psep_2025_107887 crossref_primary_10_1007_s00202_024_02388_7 crossref_primary_10_1109_ACCESS_2024_3496123 crossref_primary_10_1016_j_apm_2025_116383 crossref_primary_10_1007_s00500_024_09858_x crossref_primary_10_1016_j_cie_2024_110529 crossref_primary_10_1016_j_cma_2025_117825 crossref_primary_10_1007_s42484_023_00110_7 crossref_primary_10_1016_j_enconman_2024_118632 crossref_primary_10_1093_jcde_qwad060 crossref_primary_10_1007_s11709_025_1211_6 crossref_primary_10_1007_s00521_024_10009_4 crossref_primary_10_1007_s11227_023_05513_8 crossref_primary_10_3390_math11112591 crossref_primary_10_1007_s11042_024_19201_z crossref_primary_10_1016_j_rineng_2025_106530 crossref_primary_10_1007_s10489_023_04473_z crossref_primary_10_1007_s00500_023_09023_w crossref_primary_10_1007_s00521_023_08970_7 crossref_primary_10_1016_j_compbiomed_2023_107389 crossref_primary_10_1007_s00521_025_10982_4 crossref_primary_10_1016_j_ins_2024_120661 crossref_primary_10_1109_TTE_2024_3435998 crossref_primary_10_1007_s40430_023_04455_9 crossref_primary_10_1016_j_knosys_2024_112347 crossref_primary_10_1109_TVT_2024_3514664 crossref_primary_10_3390_act14080375 crossref_primary_10_3390_sym14112282 crossref_primary_10_3390_app14198921 crossref_primary_10_1016_j_epsr_2023_109522 crossref_primary_10_1007_s44196_025_00821_8 crossref_primary_10_1016_j_epsr_2023_109503 crossref_primary_10_1016_j_prime_2023_100153 crossref_primary_10_1080_15623599_2025_2502697 crossref_primary_10_1007_s12652_025_04969_1 crossref_primary_10_3390_biomimetics9080474 crossref_primary_10_1016_j_eswa_2025_127808 crossref_primary_10_1016_j_measurement_2025_118337 crossref_primary_10_1016_j_egyr_2023_03_036 crossref_primary_10_1016_j_heliyon_2024_e27796 crossref_primary_10_1038_s41598_025_99105_6 crossref_primary_10_1007_s41939_024_00453_z crossref_primary_10_1007_s11235_023_01063_9 crossref_primary_10_1016_j_asoc_2025_113738 crossref_primary_10_1016_j_knosys_2024_112590 crossref_primary_10_1007_s00707_023_03773_2 crossref_primary_10_1093_jcde_qwad058 crossref_primary_10_1016_j_cma_2023_116238 crossref_primary_10_3390_biomimetics10090581 crossref_primary_10_3389_fmech_2025_1547819 crossref_primary_10_1109_ACCESS_2023_3261266 |
| Cites_doi | 10.1016/j.cma.2013.10.019 10.1080/03052150008941301 10.1016/j.esr.2018.11.001 10.1016/j.ymssp.2020.106914 10.1109/TEVC.2003.814902 10.1016/j.mechmachtheory.2006.02.004 10.1007/s00158-008-0238-3 10.1016/j.advengsoft.2017.07.002 10.1016/j.advengsoft.2015.11.004 10.1145/3205651.3205796 10.1007/s00521-019-04452-x 10.1016/j.cub.2006.01.054 10.1080/0952813X.2013.782347 10.1109/MCS.2002.1004010 10.1002/(SICI)1097-0207(19960315)39:5<829::AID-NME884>3.0.CO;2-U 10.1016/j.compstruc.2016.03.001 10.1016/S1364-6613(98)01272-8 10.1016/j.advengsoft.2016.01.008 10.1016/j.knosys.2015.07.006 10.1016/S1474-0346(02)00011-3 10.1016/j.compstruc.2014.03.007 10.1016/j.eswa.2009.06.044 10.1016/j.advengsoft.2013.03.004 10.1016/j.cma.2018.01.035 10.1016/j.knosys.2018.08.030 10.1242/jeb.205.16.2325 10.1242/bio.014357 10.1098/rspb.2003.2365 10.1016/j.advengsoft.2013.12.007 10.1016/j.asoc.2004.08.004 10.1023/A:1008202821328 10.1038/scientificamerican0792-66 10.1016/j.jocs.2016.01.004 10.1016/j.advengsoft.2017.05.014 10.1080/03052150410001704854 10.1016/j.knosys.2011.07.001 10.1007/s10489-017-0951-y 10.1109/4235.585893 10.1016/j.swevo.2011.02.002 10.1016/j.cma.2020.113335 10.1080/03052150410001647966 10.1115/1.2919393 10.1016/j.asoc.2015.04.048 10.1108/02644401211235834 10.1007/s11071-019-05043-0 10.1080/01621459.1937.10503522 10.1016/S0166-3615(99)00046-9 10.1016/j.engappai.2017.09.012 10.1016/j.engappai.2019.103300 10.1016/j.knosys.2018.06.001 10.1016/j.cad.2010.12.015 10.1016/j.eswa.2020.113428 10.1016/j.ijepes.2013.03.032 10.1016/j.cma.2008.02.006 10.1145/937503.937505 10.1016/j.knosys.2016.01.009 10.1016/j.engappai.2018.04.021 10.1098/rsbl.2011.1180 10.1016/j.engappai.2019.103370 10.1016/j.ecoinf.2006.07.003 10.1016/j.fcij.2018.06.001 10.1016/j.cnsns.2012.05.010 10.1016/j.engappai.2006.03.003 10.1016/j.cma.2020.113609 10.1016/j.cma.2018.04.037 10.1016/j.eswa.2008.02.039 10.1353/ect.2012.0064 10.1007/s00366-011-0241-y 10.1016/j.compstruc.2012.07.010 10.1016/j.advengsoft.2017.01.004 10.1214/aoms/1177704575 10.1016/j.cma.2004.09.007 10.1016/j.cub.2012.04.057 10.1016/j.cnsns.2013.08.027 10.1109/ACCESS.2019.2918753 10.1016/j.swevo.2018.02.013 10.1002/cplx.21634 10.1016/j.asoc.2009.08.031 10.1016/j.asoc.2020.106367 10.1016/j.matcom.2020.12.008 10.1016/j.asoc.2012.11.026 10.1016/j.future.2019.02.028 10.1007/s00500-018-3102-4 10.1016/j.engappai.2017.01.006 10.1109/3477.484436 10.1016/j.apm.2015.10.040 10.1016/S0045-7825(01)00323-1 |
| ContentType | Journal Article |
| Copyright | 2021 Elsevier B.V. Copyright Elsevier BV Jan 1, 2022 |
| Copyright_xml | – notice: 2021 Elsevier B.V. – notice: Copyright Elsevier BV Jan 1, 2022 |
| DBID | AAYXX CITATION 7SC 7TB 8FD FR3 JQ2 KR7 L7M L~C L~D |
| DOI | 10.1016/j.cma.2021.114194 |
| DatabaseName | CrossRef Computer and Information Systems Abstracts Mechanical & Transportation Engineering Abstracts Technology Research Database Engineering Research Database ProQuest Computer Science Collection Civil Engineering Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
| DatabaseTitle | CrossRef Civil Engineering Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Engineering Research Database Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional |
| DatabaseTitleList | Civil Engineering Abstracts |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Applied Sciences Engineering |
| EISSN | 1879-2138 |
| ExternalDocumentID | 10_1016_j_cma_2021_114194 S0045782521005259 |
| GroupedDBID | --K --M -~X .DC .~1 0R~ 1B1 1~. 1~5 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAXUO AAYFN ABAOU ABBOA ABFNM ABJNI ABMAC ABYKQ ACAZW ACDAQ ACGFS ACIWK ACRLP ACZNC ADBBV ADEZE ADGUI ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIGVJ AIKHN AITUG AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD ARUGR AXJTR BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EO8 EO9 EP2 EP3 F5P FDB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ IHE J1W JJJVA KOM LG9 LY7 M41 MHUIS MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. PQQKQ Q38 RNS ROL RPZ SDF SDG SDP SES SPC SPCBC SST SSV SSW SSZ T5K TN5 WH7 XPP ZMT ~02 ~G- 29F 9DU AAQXK AATTM AAXKI AAYWO AAYXX ABEFU ABWVN ABXDB ACLOT ACNNM ACRPL ACVFH ADCNI ADIYS ADJOM ADMUD ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AI. AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP ASPBG AVWKF AZFZN CITATION EFKBS EJD FEDTE FGOYB G-2 HLZ HVGLF HZ~ R2- SBC SET SEW VH1 VOH WUQ ZY4 ~HD 7SC 7TB 8FD FR3 JQ2 KR7 L7M L~C L~D |
| ID | FETCH-LOGICAL-c368t-b5c78c7b2bc5b903cb203553a7e3d4e14e5331094fd7caca981197dd05c32f783 |
| ISICitedReferencesCount | 652 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000720455700009&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0045-7825 |
| IngestDate | Sun Nov 09 06:28:56 EST 2025 Sat Nov 29 07:29:09 EST 2025 Tue Nov 18 22:08:41 EST 2025 Fri Feb 23 02:42:31 EST 2024 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Artificial hummingbird algorithm Genetic algorithm Engineering optimization Benchmark Swarm intelligence Bio-inspired computing Algorithm Meta-heuristics |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c368t-b5c78c7b2bc5b903cb203553a7e3d4e14e5331094fd7caca981197dd05c32f783 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0001-6899-3289 |
| OpenAccessLink | http://hdl.handle.net/10072/411879 |
| PQID | 2622813538 |
| PQPubID | 2045269 |
| ParticipantIDs | proquest_journals_2622813538 crossref_primary_10_1016_j_cma_2021_114194 crossref_citationtrail_10_1016_j_cma_2021_114194 elsevier_sciencedirect_doi_10_1016_j_cma_2021_114194 |
| PublicationCentury | 2000 |
| PublicationDate | 2022-01-01 2022-01-00 20220101 |
| PublicationDateYYYYMMDD | 2022-01-01 |
| PublicationDate_xml | – month: 01 year: 2022 text: 2022-01-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | Amsterdam |
| PublicationPlace_xml | – name: Amsterdam |
| PublicationTitle | Computer methods in applied mechanics and engineering |
| PublicationYear | 2022 |
| Publisher | Elsevier B.V Elsevier BV |
| Publisher_xml | – name: Elsevier B.V – name: Elsevier BV |
| References | Yang, Deb (b25) 2010; 1 Ngo, Sadollah, Kim (b110) 2016; 13 Krishnanand, Ghose (b29) 2005 Kaveh, Farhoudi (b34) 2013; 59 Pan (b30) 2012; 26 Gandomi, Alavi (b43) 2012; 17 Hossain, Huda, Mekhilef, Seyedmahmoudian, Horan, Stojcevski, Ahmed (b114) 2018; 22 Zhao, Wang, Zhang (b7) 2019; 7 Liu, Cai, Wang (b83) 2010; 10 Zhou, Zhao, Luo, Zhou (b118) 2020 Beheshti, Shamsuddin (b1) 2011; 5 Abualigah, Diabat, Mirjalili, Abd Elaziz, Gandomi (b11) 2021; 376 H. Wang, Z. Ren, X. Li, X. Chen, H. Jiang, Solving team making problem for crowdsourcing with hybrid metaheuristic algorithm, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018, pp. 318–319. Parsopoulos, Vrahatis (b95) 2005 Mezura-Montes, Coello (b97) 2005 Coello Coello, Becerra (b91) 2004; 36 Blum, Roli (b2) 2003; 35 Mirjalili (b88) 2015; 89 Reddy, Panigrahi, Kundu, Mukherjee, Debchoudhury (b68) 2013; 53 Fister, Yang, Fister, Brest, Fister (b52) 2013 Cheng, Prayogo (b87) 2014; 139 Wang, Cai, Zhou, Fan (b84) 2009; 37 Kannan, Kramer (b107) 1994; 116 Zhang, Wang, Ji (b19) 2015; 2015 Dhiman, Kumar (b39) 2018; 159 Arora, Singh (b41) 2019; 23 Chickermane, Gea (b86) 1996; 39 Osyczka (b113) 2002 Griffiths, Dickinson, Clayton (b64) 1999; 3 Siddall (b105) 1982 Wang, Zhou, Zhou (b27) 2016 Murty (b115) 2017 dos Santos Coelho (b94) 2010; 37 Altshuler, Dudley (b60) 2002; 205 He, Wang (b93) 2007; 186 Wolpert, Macready (b54) 1997; 1 Henderson, Hurly, Bateson, Healy (b63) 2006; 16 Mirjalili, Mirjalili, Lewis (b51) 2014; 69 DeLand (b116) 2012 He, Wang (b92) 2007; 20 He, Prempain, Wu (b106) 2004; 36 Jain, Singh, Rani (b32) 2019; 44 Gandomi, Yang, Alavi (b85) 2013; 29 Ferro, Micheletti, Perotto (b10) 2020; 372 Saremi, Mirjalili, Lewis (b47) 2017; 105 Liang, Qu, Suganthan (b75) 2013 Mantere, Alander (b3) 2005; 5 Holland (b16) 1992; 267 Moosavi, Bardsiri (b44) 2017; 60 Yang, Gu, Liu, Hao, Li (b4) 2020; 145 Cheraghalipour, Hajiaghaei-Keshteli, Paydar (b38) 2018; 72 Eskandar, Sadollah, Bahreininejad, Hamdi (b111) 2012; 110 Karaboga, Akay (b22) 2009; 214 Deb, Goyal (b104) 1997 Zhang, Huang, Ding, Tang, Han, Huang (b58) 2019; 97 Darwish (b14) 2018; 3 Gogna, Tayal (b17) 2013; 25 Gupta, Deep (b57) 2020; 93 Zahara, Kao (b108) 2009; 36 Askarzadeh (b49) 2016; 169 Dorigo, Maniezzo, Colorni (b20) 1996; 26 Kennedy, Eberhart (b18) 1995 Dhiman, Kumar (b42) 2017; 114 Ward, Day, Wilkening, Wylie, Saucier, Iwaniuk (b61) 2012; 8 Yang, Deb (b24) 2009 Mehrabian, Lucas (b40) 2006; 1 Zhao, Shi, Wang, Cao, Zhang (b12) 2021; 8 Zhu, Kwong (b55) 2010; 217 Leys, Reynaerts, Vandepitte (b66) 2016; 5 Huang, Wang, He (b96) 2007; 186 Storn, Price (b67) 1997; 11 Fesanghary, Mahdavi, Minary-Jolandan, Alizadeh (b76) 2008; 197 Yang (b48) 2012 Lee, Geem (b109) 2005; 194 Derrac, García, Molina, Herrera (b72) 2011; 1 Yang, Gandomi (b28) 2012; 29 Arsham (b71) 2004; 2 Mirjalili, Gandomi, Mirjalili, Saremi, Faris, Mirjalili (b70) 2017; 114 Passino (b31) 2002; 22 Yong, Tang, Xue (b117) 2011; 31 Abedinia, Amjady, Ghasemi (b35) 2016; 21 Coello (b103) 2000; 32 E. Mezura-Montes, C.C. Coello, J. Velázquez-Reyes, Increasing successful offspring and diversity in differential evolution for engineering design, in: Proceedings of the Seventh International Conference on Adaptive Computing in Design and Manufacture, ACDM 2006, 2006, pp. 131–139. Li, Zhao, Weng, Han (b37) 2016; 92 Savsani, Savsani (b77) 2016; 40 Coello (b89) 2000; 41 Merrikh-Bayat (b45) 2015; 33 Warrick, Hedrick, Fernandez, Tobalske, Biewener (b65) 2012; 22 Xia, Zhang, Xia, Shi (b80) 2018; 333 Ewees, Abd Elaziz (b99) 2020; 88 Askarzadeh (b46) 2014; 19 Rao, Savsani, Vakharia (b100) 2011; 43 Zhao, Wang, Zhang (b5) 2019; 163 Friedman (b73) 1937; 32 Yan, Li (b23) 2011; 7 Meng, Pan (b50) 2016; 97 Zhao, Du, Jiang (b13) 2018; 339 Bateson, Healy, Hurly (b62) 2003; 270 Rodríguez-Esparza, Zanella-Calzada, Oliva, Heidari, Zaldivar, Pérez-Cisneros, Foong (b8) 2020; 155 Mirjalili, Lewis (b36) 2016; 95 Hatamlou (b15) 2017; 47 Coello, Montes (b90) 2002; 16 Ab Wahab, Nefti-Meziani, Atyabi (b21) 2015; 10 Rao, Tiwari (b98) 2007; 42 Doush, Santos (b9) 2019 Sadollah, Bahreininejad, Eskandar, Hamdi (b101) 2013; 13 Yin, Liu, Zhang, Teng (b26) 2016; 12 Gong, Cai, Liang (b102) 2014; 268 Yan, Zhang, Zeng, Tang (b56) 2021; 185 Hodges, Lehmann (b74) 1962; 33 Coello (b79) 2002; 191 Zhao, Wang, Zhang (b33) 2020; 32 Zhao, Zhang, Wang (b81) 2020; 87 Ray, Liew (b82) 2003; 7 Jaddi, Abdullah (b53) 2018; 67 Tanabe, Fukunaga (b69) 2013 Heidari, Mirjalili, Faris, Aljarah, Mafarja, Chen (b78) 2019; 97 Fennelly (b59) 2012; 8 Askarzadeh (10.1016/j.cma.2021.114194_b49) 2016; 169 Deb (10.1016/j.cma.2021.114194_b104) 1997 Dorigo (10.1016/j.cma.2021.114194_b20) 1996; 26 Coello (10.1016/j.cma.2021.114194_b90) 2002; 16 Sadollah (10.1016/j.cma.2021.114194_b101) 2013; 13 Yang (10.1016/j.cma.2021.114194_b4) 2020; 145 Yan (10.1016/j.cma.2021.114194_b23) 2011; 7 Zhao (10.1016/j.cma.2021.114194_b81) 2020; 87 Wang (10.1016/j.cma.2021.114194_b84) 2009; 37 Zahara (10.1016/j.cma.2021.114194_b108) 2009; 36 Leys (10.1016/j.cma.2021.114194_b66) 2016; 5 Coello (10.1016/j.cma.2021.114194_b103) 2000; 32 Fennelly (10.1016/j.cma.2021.114194_b59) 2012; 8 Holland (10.1016/j.cma.2021.114194_b16) 1992; 267 Reddy (10.1016/j.cma.2021.114194_b68) 2013; 53 He (10.1016/j.cma.2021.114194_b92) 2007; 20 Gong (10.1016/j.cma.2021.114194_b102) 2014; 268 Hossain (10.1016/j.cma.2021.114194_b114) 2018; 22 Fister (10.1016/j.cma.2021.114194_b52) 2013 Zhao (10.1016/j.cma.2021.114194_b12) 2021; 8 Griffiths (10.1016/j.cma.2021.114194_b64) 1999; 3 Yang (10.1016/j.cma.2021.114194_b28) 2012; 29 Zhang (10.1016/j.cma.2021.114194_b58) 2019; 97 Ewees (10.1016/j.cma.2021.114194_b99) 2020; 88 Darwish (10.1016/j.cma.2021.114194_b14) 2018; 3 Rao (10.1016/j.cma.2021.114194_b100) 2011; 43 Askarzadeh (10.1016/j.cma.2021.114194_b46) 2014; 19 Xia (10.1016/j.cma.2021.114194_b80) 2018; 333 Siddall (10.1016/j.cma.2021.114194_b105) 1982 Blum (10.1016/j.cma.2021.114194_b2) 2003; 35 Jain (10.1016/j.cma.2021.114194_b32) 2019; 44 Zhao (10.1016/j.cma.2021.114194_b5) 2019; 163 Kannan (10.1016/j.cma.2021.114194_b107) 1994; 116 Friedman (10.1016/j.cma.2021.114194_b73) 1937; 32 Mirjalili (10.1016/j.cma.2021.114194_b88) 2015; 89 Fesanghary (10.1016/j.cma.2021.114194_b76) 2008; 197 Mirjalili (10.1016/j.cma.2021.114194_b36) 2016; 95 Savsani (10.1016/j.cma.2021.114194_b77) 2016; 40 Altshuler (10.1016/j.cma.2021.114194_b60) 2002; 205 Hodges (10.1016/j.cma.2021.114194_b74) 1962; 33 Ray (10.1016/j.cma.2021.114194_b82) 2003; 7 He (10.1016/j.cma.2021.114194_b93) 2007; 186 Parsopoulos (10.1016/j.cma.2021.114194_b95) 2005 Zhao (10.1016/j.cma.2021.114194_b7) 2019; 7 Kennedy (10.1016/j.cma.2021.114194_b18) 1995 Warrick (10.1016/j.cma.2021.114194_b65) 2012; 22 Coello Coello (10.1016/j.cma.2021.114194_b91) 2004; 36 10.1016/j.cma.2021.114194_b112 Yang (10.1016/j.cma.2021.114194_b24) 2009 Tanabe (10.1016/j.cma.2021.114194_b69) 2013 Zhang (10.1016/j.cma.2021.114194_b19) 2015; 2015 Zhou (10.1016/j.cma.2021.114194_b118) 2020 Arora (10.1016/j.cma.2021.114194_b41) 2019; 23 Coello (10.1016/j.cma.2021.114194_b79) 2002; 191 Pan (10.1016/j.cma.2021.114194_b30) 2012; 26 Mirjalili (10.1016/j.cma.2021.114194_b70) 2017; 114 Huang (10.1016/j.cma.2021.114194_b96) 2007; 186 Mantere (10.1016/j.cma.2021.114194_b3) 2005; 5 Gogna (10.1016/j.cma.2021.114194_b17) 2013; 25 Meng (10.1016/j.cma.2021.114194_b50) 2016; 97 Kaveh (10.1016/j.cma.2021.114194_b34) 2013; 59 Hatamlou (10.1016/j.cma.2021.114194_b15) 2017; 47 DeLand (10.1016/j.cma.2021.114194_b116) 2012 Ferro (10.1016/j.cma.2021.114194_b10) 2020; 372 dos Santos Coelho (10.1016/j.cma.2021.114194_b94) 2010; 37 Cheng (10.1016/j.cma.2021.114194_b87) 2014; 139 Coello (10.1016/j.cma.2021.114194_b89) 2000; 41 Karaboga (10.1016/j.cma.2021.114194_b22) 2009; 214 Gandomi (10.1016/j.cma.2021.114194_b85) 2013; 29 Gandomi (10.1016/j.cma.2021.114194_b43) 2012; 17 Dhiman (10.1016/j.cma.2021.114194_b42) 2017; 114 Mezura-Montes (10.1016/j.cma.2021.114194_b97) 2005 Doush (10.1016/j.cma.2021.114194_b9) 2019 Zhu (10.1016/j.cma.2021.114194_b55) 2010; 217 Beheshti (10.1016/j.cma.2021.114194_b1) 2011; 5 Henderson (10.1016/j.cma.2021.114194_b63) 2006; 16 Ward (10.1016/j.cma.2021.114194_b61) 2012; 8 Osyczka (10.1016/j.cma.2021.114194_b113) 2002 Heidari (10.1016/j.cma.2021.114194_b78) 2019; 97 Zhao (10.1016/j.cma.2021.114194_b13) 2018; 339 Zhao (10.1016/j.cma.2021.114194_b33) 2020; 32 Li (10.1016/j.cma.2021.114194_b37) 2016; 92 Chickermane (10.1016/j.cma.2021.114194_b86) 1996; 39 Lee (10.1016/j.cma.2021.114194_b109) 2005; 194 Mehrabian (10.1016/j.cma.2021.114194_b40) 2006; 1 Abedinia (10.1016/j.cma.2021.114194_b35) 2016; 21 Gupta (10.1016/j.cma.2021.114194_b57) 2020; 93 Abualigah (10.1016/j.cma.2021.114194_b11) 2021; 376 Cheraghalipour (10.1016/j.cma.2021.114194_b38) 2018; 72 Mirjalili (10.1016/j.cma.2021.114194_b51) 2014; 69 10.1016/j.cma.2021.114194_b6 Rodríguez-Esparza (10.1016/j.cma.2021.114194_b8) 2020; 155 Dhiman (10.1016/j.cma.2021.114194_b39) 2018; 159 Yang (10.1016/j.cma.2021.114194_b48) 2012 Eskandar (10.1016/j.cma.2021.114194_b111) 2012; 110 Murty (10.1016/j.cma.2021.114194_b115) 2017 Derrac (10.1016/j.cma.2021.114194_b72) 2011; 1 Rao (10.1016/j.cma.2021.114194_b98) 2007; 42 Yong (10.1016/j.cma.2021.114194_b117) 2011; 31 Merrikh-Bayat (10.1016/j.cma.2021.114194_b45) 2015; 33 He (10.1016/j.cma.2021.114194_b106) 2004; 36 Yin (10.1016/j.cma.2021.114194_b26) 2016; 12 Yang (10.1016/j.cma.2021.114194_b25) 2010; 1 Saremi (10.1016/j.cma.2021.114194_b47) 2017; 105 Yan (10.1016/j.cma.2021.114194_b56) 2021; 185 Passino (10.1016/j.cma.2021.114194_b31) 2002; 22 Moosavi (10.1016/j.cma.2021.114194_b44) 2017; 60 Liu (10.1016/j.cma.2021.114194_b83) 2010; 10 Liang (10.1016/j.cma.2021.114194_b75) 2013 Bateson (10.1016/j.cma.2021.114194_b62) 2003; 270 Wang (10.1016/j.cma.2021.114194_b27) 2016 Storn (10.1016/j.cma.2021.114194_b67) 1997; 11 Wolpert (10.1016/j.cma.2021.114194_b54) 1997; 1 Arsham (10.1016/j.cma.2021.114194_b71) 2004; 2 Ngo (10.1016/j.cma.2021.114194_b110) 2016; 13 Krishnanand (10.1016/j.cma.2021.114194_b29) 2005 Ab Wahab (10.1016/j.cma.2021.114194_b21) 2015; 10 Jaddi (10.1016/j.cma.2021.114194_b53) 2018; 67 |
| References_xml | – volume: 110 start-page: 151 year: 2012 end-page: 166 ident: b111 article-title: Water cycle algorithm–A novel metaheuristic optimization method for solving constrained engineering optimization problems publication-title: Comput. Struct. – volume: 339 start-page: 341 year: 2018 end-page: 357 ident: b13 article-title: An adaptive multiscale approach for identifying multiple flaws based on XFEM and a discrete artificial fish swarm algorithm publication-title: Comput. Methods Appl. Mech. Engrg. – volume: 205 start-page: 2325 year: 2002 end-page: 2336 ident: b60 article-title: The ecological and evolutionary interface of hummingbird flight physiology publication-title: J. Exp. Biol. – volume: 270 start-page: 1271 year: 2003 end-page: 1276 ident: b62 article-title: Context–dependent foraging decisions in rufous hummingbirds publication-title: Proc. R. Soc. B – start-page: 652 year: 2005 end-page: 662 ident: b97 article-title: Useful infeasible solutions in engineering optimization with evolutionary algorithms publication-title: Mexican International Conference on Artificial Intelligence – volume: 145 year: 2020 ident: b4 article-title: A general multi-objective optimized wavelet filter and its applications in fault diagnosis of wheelset bearings publication-title: Mech. Syst. Signal Process. – volume: 159 start-page: 20 year: 2018 end-page: 50 ident: b39 article-title: Emperor penguin optimizer: A bio-inspired algorithm for engineering problems publication-title: Knowl.-Based Syst. – start-page: 276 year: 2019 end-page: 284 ident: b9 article-title: A sensitivity analysis for harmony search with multi-parent crossover algorithm publication-title: Proceedings of SAI Intelligent Systems Conference – volume: 1 start-page: 3 year: 2011 end-page: 18 ident: b72 article-title: A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms publication-title: Swarm Evol. Comput. – volume: 186 start-page: 1407 year: 2007 end-page: 1422 ident: b93 article-title: A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization publication-title: Appl. Math. Comput. – volume: 43 start-page: 303 year: 2011 end-page: 315 ident: b100 article-title: Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems publication-title: Comput. Aided Des. – year: 2012 ident: b116 article-title: Solving large-scale optimization problems with MATLAB: A hydroelectric flow example – volume: 7 start-page: 386 year: 2003 end-page: 396 ident: b82 article-title: Society and civilization: an optimization algorithm based on the simulation of social behavior publication-title: IEEE Trans. Evol. Comput. – volume: 20 start-page: 89 year: 2007 end-page: 99 ident: b92 article-title: An effective co-evolutionary particle swarm optimization for constrained engineering design problems publication-title: Eng. Appl. Artif. Intell. – volume: 5 start-page: 1 year: 2011 end-page: 35 ident: b1 article-title: A review of population-based meta-heuristic algorithms publication-title: Int. J. Adv. Soft Comput. Appl. – volume: 36 start-page: 3880 year: 2009 end-page: 3886 ident: b108 article-title: Hybrid Nelder–Mead simplex search and particle swarm optimization for constrained engineering design problems publication-title: Expert Syst. Appl. – reference: H. Wang, Z. Ren, X. Li, X. Chen, H. Jiang, Solving team making problem for crowdsourcing with hybrid metaheuristic algorithm, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018, pp. 318–319. – volume: 5 start-page: 315 year: 2005 end-page: 331 ident: b3 article-title: Evolutionary software engineering, a review publication-title: Appl. Soft Comput. – volume: 114 start-page: 48 year: 2017 end-page: 70 ident: b42 article-title: Spotted hyena optimizer: a novel bio-inspired based metaheuristic technique for engineering applications publication-title: Adv. Eng. Softw. – volume: 268 start-page: 884 year: 2014 end-page: 904 ident: b102 article-title: Engineering optimization by means of an improved constrained differential evolution publication-title: Comput. Methods Appl. Mech. Engrg. – volume: 2015 year: 2015 ident: b19 article-title: A comprehensive survey on particle swarm optimization algorithm and its applications publication-title: Math. Probl. Eng. – volume: 13 start-page: 2592 year: 2013 end-page: 2612 ident: b101 article-title: Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems publication-title: Appl. Soft Comput. – volume: 376 year: 2021 ident: b11 article-title: The arithmetic optimization algorithm publication-title: Comput. Methods Appl. Mech. Engrg. – volume: 1 start-page: 67 year: 1997 end-page: 82 ident: b54 article-title: No free lunch theorems for optimization publication-title: IEEE Trans. Evol. Comput. – start-page: 210 year: 2009 end-page: 214 ident: b24 article-title: Cuckoo search via Lévy flights publication-title: 2009 World Congress on Nature & Biologically Inspired Computing – volume: 105 start-page: 30 year: 2017 end-page: 47 ident: b47 article-title: Grasshopper optimisation algorithm: theory and application publication-title: Adv. Eng. Softw. – reference: E. Mezura-Montes, C.C. Coello, J. Velázquez-Reyes, Increasing successful offspring and diversity in differential evolution for engineering design, in: Proceedings of the Seventh International Conference on Adaptive Computing in Design and Manufacture, ACDM 2006, 2006, pp. 131–139. – volume: 333 start-page: 356 year: 2018 end-page: 370 ident: b80 article-title: Stress-based topology optimization using bi-directional evolutionary structural optimization method publication-title: Comput. Methods Appl. Mech. Engrg. – volume: 41 start-page: 113 year: 2000 end-page: 127 ident: b89 article-title: Use of a self-adaptive penalty approach for engineering optimization problems publication-title: Comput. Ind. – volume: 22 start-page: 426 year: 2018 end-page: 437 ident: b114 article-title: A state-of-the-art review of hydropower in Malaysia as renewable energy: Current status and future prospects publication-title: Energy Strategy Rev. – volume: 139 start-page: 98 year: 2014 end-page: 112 ident: b87 article-title: Symbiotic organisms search: a new metaheuristic optimization algorithm publication-title: Comput. Struct. – start-page: 84 year: 2005 end-page: 91 ident: b29 article-title: Detection of multiple source locations using a glowworm metaphor with applications to collective robotics publication-title: Proceedings 2005 IEEE Swarm Intelligence Symposium – volume: 72 start-page: 393 year: 2018 end-page: 414 ident: b38 article-title: Tree growth algorithm (TGA): A novel approach for solving optimization problems publication-title: Eng. Appl. Artif. Intell. – volume: 116 start-page: 405 year: 1994 end-page: 411 ident: b107 article-title: An augmented Lagrange multiplier based method for mixed integer discrete continuous optimization and its applications to mechanical design publication-title: J. Mech. Des. – year: 2002 ident: b113 article-title: Evolutionary Algorithms for Single and Multicriteria Design Optimization: Studies in Fuzzyness and Soft Computing – volume: 163 start-page: 283 year: 2019 end-page: 304 ident: b5 article-title: Atom search optimization and its application to solve a hydrogeologic parameter estimation problem publication-title: Knowl.-Based Syst. – volume: 217 start-page: 3166 year: 2010 end-page: 3173 ident: b55 article-title: Gbest-guided artificial bee colony algorithm for numerical function optimization publication-title: Appl. Math. Comput. – year: 2013 ident: b52 article-title: A brief review of nature-inspired algorithms for optimization – volume: 92 start-page: 65 year: 2016 end-page: 88 ident: b37 article-title: A novel nature-inspired algorithm for optimization: Virus colony search publication-title: Adv. Eng. Softw. – volume: 31 start-page: 1118 year: 2011 end-page: 1125 ident: b117 article-title: Optimal operation of cascade reservoirs based on improved artificial fish swarm algorithm publication-title: Syst. Eng. Theory Pract. – start-page: 1942 year: 1995 end-page: 1948 ident: b18 article-title: Particle swarm optimization publication-title: Proceedings of ICNN’95-International Conference on Neural Networks, Vol. 4 – volume: 169 start-page: 1 year: 2016 end-page: 12 ident: b49 article-title: A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm publication-title: Comput. Struct. – start-page: 521 year: 1997 end-page: 528 ident: b104 article-title: Optimizing engineering designs using a combined genetic search publication-title: ICGA – volume: 39 start-page: 829 year: 1996 end-page: 846 ident: b86 article-title: Structural optimization using a new local approximation method publication-title: Internat. J. Numer. Methods Engrg. – volume: 10 year: 2015 ident: b21 article-title: A comprehensive review of swarm optimization algorithms publication-title: PLoS One – volume: 32 start-page: 9383 year: 2020 end-page: 9425 ident: b33 article-title: Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm publication-title: Neural Comput. Appl. – volume: 114 start-page: 163 year: 2017 end-page: 191 ident: b70 article-title: Salp swarm algorithm: A bio-inspired optimizer for engineering design problems publication-title: Adv. Eng. Softw. – volume: 60 start-page: 1 year: 2017 end-page: 15 ident: b44 article-title: Satin bowerbird optimizer: A new optimization algorithm to optimize ANFIS for software development effort estimation publication-title: Eng. Appl. Artif. Intell. – volume: 17 start-page: 4831 year: 2012 end-page: 4845 ident: b43 article-title: Krill herd: A new bio-inspired optimization algorithm publication-title: Commun. Nonlinear Sci. Numer. Simul. – start-page: 71 year: 2013 end-page: 78 ident: b69 article-title: Success-history based parameter adaptation for differential evolution publication-title: 2013 IEEE Congress on Evolutionary Computation – volume: 29 start-page: 17 year: 2013 end-page: 35 ident: b85 article-title: Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems publication-title: Eng. Comput. – volume: 93 year: 2020 ident: b57 article-title: A memory-based grey wolf optimizer for global optimization tasks publication-title: Appl. Soft Comput. – volume: 11 start-page: 341 year: 1997 end-page: 359 ident: b67 article-title: Differential evolution–A simple and efficient heuristic for global optimization over continuous spaces publication-title: J. Global Optim. – volume: 26 start-page: 29 year: 1996 end-page: 41 ident: b20 article-title: Ant system: optimization by a colony of cooperating agents publication-title: IEEE Trans. Syst. Man Cybern. B – volume: 214 start-page: 108 year: 2009 end-page: 132 ident: b22 article-title: A comparative study of artificial bee colony algorithm publication-title: Appl. Math. Comput. – year: 2020 ident: b118 article-title: Optimal hydropower station dispatch using quantum social spider optimization algorithm publication-title: Concurr. Comput.: Pract. Exper. – volume: 97 start-page: 1227 year: 2019 end-page: 1243 ident: b58 article-title: Hummingbirds optimization algorithm-based particle filter for maneuvering target tracking publication-title: Nonlinear Dynam. – start-page: 582 year: 2005 end-page: 591 ident: b95 article-title: Unified particle swarm optimization for solving constrained engineering optimization problems publication-title: International Conference on Natural Computation – volume: 1 start-page: 355 year: 2006 end-page: 366 ident: b40 article-title: A novel numerical optimization algorithm inspired from weed colonization publication-title: Ecol. Inform. – volume: 26 start-page: 69 year: 2012 end-page: 74 ident: b30 article-title: A new fruit fly optimization algorithm: taking the financial distress model as an example publication-title: Knowl.-Based Syst. – volume: 89 start-page: 228 year: 2015 end-page: 249 ident: b88 article-title: Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm publication-title: Knowl.-Based Syst. – volume: 8 start-page: 1204 year: 2021 end-page: 1233 ident: b12 article-title: An adaptive hybrid atom search optimization with particle swarm optimization and its application to optimal no-load PID design of hydro-turbine governor publication-title: J. comput. Des. Eng. – volume: 3 start-page: 231 year: 2018 end-page: 246 ident: b14 article-title: Bio-inspired computing: Algorithms review, deep analysis, and the scope of applications publication-title: Future Comput. Inform. J. – volume: 95 start-page: 51 year: 2016 end-page: 67 ident: b36 article-title: The whale optimization algorithm publication-title: Adv. Eng. Softw. – volume: 33 start-page: 482 year: 1962 end-page: 497 ident: b74 article-title: Rank methods for combination of independent experiments in analysis of variance publication-title: Ann. Math. Stat. – volume: 35 start-page: 268 year: 2003 end-page: 308 ident: b2 article-title: Meta-heuristics in combinatorial optimization: Overview and conceptual comparison publication-title: ACM Comput. Surv. – volume: 22 start-page: 52 year: 2002 end-page: 67 ident: b31 article-title: Biomimicry of bacterial foraging for distributed optimization and control publication-title: IEEE Control Syst. Mag. – volume: 67 start-page: 246 year: 2018 end-page: 259 ident: b53 article-title: Optimization of neural network using kidney-inspired algorithm with control of filtration rate and chaotic map for real-world rainfall forecasting publication-title: Eng. Appl. Artif. Intell. – volume: 29 start-page: 464 year: 2012 end-page: 483 ident: b28 article-title: Bat algorithm: a novel approach for global engineering optimization publication-title: Eng. Comput. – volume: 194 start-page: 3902 year: 2005 end-page: 3933 ident: b109 article-title: A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice publication-title: Comput. Methods Appl. Mech. Engrg. – volume: 3 start-page: 74 year: 1999 end-page: 80 ident: b64 article-title: Episodic memory: what can animals remember about their past? publication-title: Trends Cogn. Sci. – volume: 37 start-page: 395 year: 2009 end-page: 413 ident: b84 article-title: Constrained optimization based on hybrid evolutionary algorithm and adaptive constraint-handling technique publication-title: Struct. Multidiscip. Optim. – volume: 197 start-page: 3080 year: 2008 end-page: 3091 ident: b76 article-title: Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems publication-title: Comput. Methods Appl. Mech. Engrg. – volume: 5 start-page: 1052 year: 2016 end-page: 1060 ident: b66 article-title: Outperforming hummingbirds’ load-lifting capability with a lightweight hummingbird-like flapping-wing mechanism publication-title: Biol. Open – volume: 32 start-page: 275 year: 2000 end-page: 308 ident: b103 article-title: Treating constraints as objectives for single-objective evolutionary optimization publication-title: Eng. Optim. A35 – start-page: 240 year: 2012 end-page: 249 ident: b48 article-title: Flower pollination algorithm for global optimization publication-title: International Conference on Unconventional Computing and Natural Computation – volume: 69 start-page: 46 year: 2014 end-page: 61 ident: b51 article-title: Grey wolf optimizer publication-title: Adv. Eng. Softw. – volume: 7 start-page: 3309 year: 2011 end-page: 3316 ident: b23 article-title: An effective refinement artificial bee colony optimization algorithm based on chaotic search and application for PID control tuning publication-title: J. Comput. Inf Syst. – start-page: 1 year: 2016 end-page: 8 ident: b27 article-title: An improved cuckoo search optimization algorithm for the problem of chaotic systems parameter estimation publication-title: Comput. Intell. Neurosci. – volume: 47 start-page: 1059 year: 2017 end-page: 1067 ident: b15 article-title: A hybrid bio-inspired algorithm and its application publication-title: Appl. Intell. – volume: 42 start-page: 233 year: 2007 end-page: 250 ident: b98 article-title: Optimum design of rolling element bearings using genetic algorithms publication-title: Mech. Mach. Theory – volume: 97 start-page: 849 year: 2019 end-page: 872 ident: b78 article-title: Harris hawks optimization: Algorithm and applications publication-title: Future Gener. Comput. Syst. – volume: 53 start-page: 113 year: 2013 end-page: 122 ident: b68 article-title: Energy and spinning reserve scheduling for a wind-thermal power system using CMA-ES with mean learning technique publication-title: Int. J. Electr. Power Energy Syst. – volume: 44 start-page: 148 year: 2019 end-page: 175 ident: b32 article-title: A novel nature-inspired algorithm for optimization: Squirrel search algorithm publication-title: Swarm Evol. Comput. – volume: 186 start-page: 340 year: 2007 end-page: 356 ident: b96 article-title: An effective co-evolutionary differential evolution for constrained optimization publication-title: Appl. Math. Comput. – year: 1982 ident: b105 article-title: Optimal Engineering Design: Principles and Applications – volume: 32 start-page: 675 year: 1937 end-page: 701 ident: b73 article-title: The use of ranks to avoid the assumption of normality implicit in the analysis of variance publication-title: J. Amer. Statist. Assoc. – volume: 16 start-page: 193 year: 2002 end-page: 203 ident: b90 article-title: Constraint-handling in genetic algorithms through the use of dominance-based tournament selection publication-title: Adv. Eng. Inform. – volume: 155 year: 2020 ident: b8 article-title: An efficient Harris hawks-inspired image segmentation method publication-title: Expert Syst. Appl. – volume: 12 start-page: 1809 year: 2016 end-page: 1819 ident: b26 article-title: Cuckoo search algorithm based on mobile cloud model publication-title: Int. J. Innovative Comput. Inf. Control – volume: 21 start-page: 97 year: 2016 end-page: 116 ident: b35 article-title: A new metaheuristic algorithm based on shark smell optimization publication-title: Complexity – volume: 267 start-page: 66 year: 1992 end-page: 73 ident: b16 article-title: Genetic algorithms publication-title: Sci. Am. – volume: 22 start-page: R472 year: 2012 end-page: R477 ident: b65 article-title: Hummingbird flight publication-title: Curr. Biol. – volume: 97 start-page: 144 year: 2016 end-page: 157 ident: b50 article-title: Monkey king evolution: A new memetic evolutionary algorithm and its application in vehicle fuel consumption optimization publication-title: Knowl.-Based Syst. – volume: 87 year: 2020 ident: b81 article-title: Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications publication-title: Eng. Appl. Artif. Intell. – volume: 88 year: 2020 ident: b99 article-title: Performance analysis of chaotic multi-verse harris hawks optimization: a case study on solving engineering problems publication-title: Eng. Appl. Artif. Intell. – volume: 40 start-page: 3951 year: 2016 end-page: 3978 ident: b77 article-title: Passing vehicle search (PVS): A novel metaheuristic algorithm publication-title: Appl. Math. Model. – volume: 13 start-page: 68 year: 2016 end-page: 82 ident: b110 article-title: A cooperative particle swarm optimizer with stochastic movements for computationally expensive numerical optimization problems publication-title: J. Comput. Sci. – volume: 372 year: 2020 ident: b10 article-title: An optimization algorithm for automatic structural design publication-title: Comput. Methods Appl. Mech. Engrg. – volume: 23 start-page: 715 year: 2019 end-page: 734 ident: b41 article-title: Butterfly optimization algorithm: a novel approach for global optimization publication-title: Soft Comput. – volume: 8 start-page: 657 year: 2012 end-page: 659 ident: b61 article-title: Hummingbirds have a greatly enlarged hippocampal formation publication-title: Biol. Lett. – volume: 10 start-page: 629 year: 2010 end-page: 640 ident: b83 article-title: Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization publication-title: Appl. Soft Comput. – volume: 2 start-page: 27 year: 2004 end-page: 53 ident: b71 article-title: Global optima for linearly constrained business decision models publication-title: Sci. J. Adm. – start-page: 783 year: 2017 end-page: 800 ident: b115 article-title: Chapter 24 - Renewable energy sources publication-title: Electrical Power Systems – start-page: 490 year: 2013 ident: b75 article-title: Problem Definitions and Evaluation Criteria for the CEC 2014 Special Session and Competition on Single Objective Real-Parameter Numerical Optimization – volume: 36 start-page: 219 year: 2004 end-page: 236 ident: b91 article-title: Efficient evolutionary optimization through the use of a cultural algorithm publication-title: Eng. Optim. – volume: 185 start-page: 17 year: 2021 end-page: 46 ident: b56 article-title: Nature-inspired approach: An enhanced whale optimization algorithm for global optimization publication-title: Math. Comput. Simulation – volume: 59 start-page: 53 year: 2013 end-page: 70 ident: b34 article-title: A new optimization method: Dolphin echolocation publication-title: Adv. Eng. Softw. – volume: 33 start-page: 292 year: 2015 end-page: 303 ident: b45 article-title: The runner-root algorithm: A metaheuristic for solving unimodal and multimodal optimization problems inspired by runners and roots of plants in nature publication-title: Appl. Soft Comput. – volume: 37 start-page: 1676 year: 2010 end-page: 1683 ident: b94 article-title: Gaussian quantum-behaved particle swarm optimization approaches for constrained engineering design problems publication-title: Expert Syst. Appl. – volume: 25 start-page: 503 year: 2013 end-page: 526 ident: b17 article-title: Metaheuristics: review and application publication-title: J. Exp. Theor. Artif. Intell. – volume: 19 start-page: 1213 year: 2014 end-page: 1228 ident: b46 article-title: Bird mating optimizer: an optimization algorithm inspired by bird mating strategies publication-title: Commun. Nonlinear Sci. Numer. Simul. – volume: 8 start-page: 74 year: 2012 end-page: 85 ident: b59 article-title: Observations from the jewel rooms publication-title: Ecotone – volume: 191 start-page: 1245 year: 2002 end-page: 1287 ident: b79 article-title: Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art publication-title: Comput. Methods Appl. Mech. Engrg. – volume: 36 start-page: 585 year: 2004 end-page: 605 ident: b106 article-title: An improved particle swarm optimizer for mechanical design optimization problems publication-title: Eng. Optim. – volume: 7 start-page: 73182 year: 2019 end-page: 73206 ident: b7 article-title: Supply-demand-based optimization: a novel economics-inspired algorithm for global optimization publication-title: IEEE Access – volume: 16 start-page: 512 year: 2006 end-page: 515 ident: b63 article-title: Timing in free-living rufous hummingbirds, publication-title: Curr. Biol. – volume: 1 start-page: 330 year: 2010 end-page: 343 ident: b25 article-title: Engineering optimisation by cuckoo search publication-title: Int. J. Math. Model. Numer. Optim. – start-page: 783 year: 2017 ident: 10.1016/j.cma.2021.114194_b115 article-title: Chapter 24 - Renewable energy sources – volume: 268 start-page: 884 year: 2014 ident: 10.1016/j.cma.2021.114194_b102 article-title: Engineering optimization by means of an improved constrained differential evolution publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/j.cma.2013.10.019 – volume: 32 start-page: 275 issue: 3 year: 2000 ident: 10.1016/j.cma.2021.114194_b103 article-title: Treating constraints as objectives for single-objective evolutionary optimization publication-title: Eng. Optim. A35 doi: 10.1080/03052150008941301 – volume: 22 start-page: 426 year: 2018 ident: 10.1016/j.cma.2021.114194_b114 article-title: A state-of-the-art review of hydropower in Malaysia as renewable energy: Current status and future prospects publication-title: Energy Strategy Rev. doi: 10.1016/j.esr.2018.11.001 – volume: 145 year: 2020 ident: 10.1016/j.cma.2021.114194_b4 article-title: A general multi-objective optimized wavelet filter and its applications in fault diagnosis of wheelset bearings publication-title: Mech. Syst. Signal Process. doi: 10.1016/j.ymssp.2020.106914 – volume: 7 start-page: 386 issue: 4 year: 2003 ident: 10.1016/j.cma.2021.114194_b82 article-title: Society and civilization: an optimization algorithm based on the simulation of social behavior publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2003.814902 – volume: 42 start-page: 233 issue: 2 year: 2007 ident: 10.1016/j.cma.2021.114194_b98 article-title: Optimum design of rolling element bearings using genetic algorithms publication-title: Mech. Mach. Theory doi: 10.1016/j.mechmachtheory.2006.02.004 – volume: 5 start-page: 1 issue: 1 year: 2011 ident: 10.1016/j.cma.2021.114194_b1 article-title: A review of population-based meta-heuristic algorithms publication-title: Int. J. Adv. Soft Comput. Appl. – volume: 37 start-page: 395 issue: 4 year: 2009 ident: 10.1016/j.cma.2021.114194_b84 article-title: Constrained optimization based on hybrid evolutionary algorithm and adaptive constraint-handling technique publication-title: Struct. Multidiscip. Optim. doi: 10.1007/s00158-008-0238-3 – volume: 114 start-page: 163 year: 2017 ident: 10.1016/j.cma.2021.114194_b70 article-title: Salp swarm algorithm: A bio-inspired optimizer for engineering design problems publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2017.07.002 – volume: 92 start-page: 65 year: 2016 ident: 10.1016/j.cma.2021.114194_b37 article-title: A novel nature-inspired algorithm for optimization: Virus colony search publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2015.11.004 – ident: 10.1016/j.cma.2021.114194_b6 doi: 10.1145/3205651.3205796 – volume: 32 start-page: 9383 issue: 13 year: 2020 ident: 10.1016/j.cma.2021.114194_b33 article-title: Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm publication-title: Neural Comput. Appl. doi: 10.1007/s00521-019-04452-x – volume: 16 start-page: 512 issue: 5 year: 2006 ident: 10.1016/j.cma.2021.114194_b63 article-title: Timing in free-living rufous hummingbirds, Selasphorus rufus publication-title: Curr. Biol. doi: 10.1016/j.cub.2006.01.054 – volume: 25 start-page: 503 issue: 4 year: 2013 ident: 10.1016/j.cma.2021.114194_b17 article-title: Metaheuristics: review and application publication-title: J. Exp. Theor. Artif. Intell. doi: 10.1080/0952813X.2013.782347 – volume: 22 start-page: 52 issue: 3 year: 2002 ident: 10.1016/j.cma.2021.114194_b31 article-title: Biomimicry of bacterial foraging for distributed optimization and control publication-title: IEEE Control Syst. Mag. doi: 10.1109/MCS.2002.1004010 – start-page: 84 year: 2005 ident: 10.1016/j.cma.2021.114194_b29 article-title: Detection of multiple source locations using a glowworm metaphor with applications to collective robotics – year: 2012 ident: 10.1016/j.cma.2021.114194_b116 – volume: 39 start-page: 829 issue: 5 year: 1996 ident: 10.1016/j.cma.2021.114194_b86 article-title: Structural optimization using a new local approximation method publication-title: Internat. J. Numer. Methods Engrg. doi: 10.1002/(SICI)1097-0207(19960315)39:5<829::AID-NME884>3.0.CO;2-U – volume: 169 start-page: 1 year: 2016 ident: 10.1016/j.cma.2021.114194_b49 article-title: A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm publication-title: Comput. Struct. doi: 10.1016/j.compstruc.2016.03.001 – volume: 3 start-page: 74 issue: 2 year: 1999 ident: 10.1016/j.cma.2021.114194_b64 article-title: Episodic memory: what can animals remember about their past? publication-title: Trends Cogn. Sci. doi: 10.1016/S1364-6613(98)01272-8 – volume: 95 start-page: 51 year: 2016 ident: 10.1016/j.cma.2021.114194_b36 article-title: The whale optimization algorithm publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2016.01.008 – volume: 89 start-page: 228 year: 2015 ident: 10.1016/j.cma.2021.114194_b88 article-title: Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2015.07.006 – volume: 16 start-page: 193 issue: 3 year: 2002 ident: 10.1016/j.cma.2021.114194_b90 article-title: Constraint-handling in genetic algorithms through the use of dominance-based tournament selection publication-title: Adv. Eng. Inform. doi: 10.1016/S1474-0346(02)00011-3 – volume: 139 start-page: 98 year: 2014 ident: 10.1016/j.cma.2021.114194_b87 article-title: Symbiotic organisms search: a new metaheuristic optimization algorithm publication-title: Comput. Struct. doi: 10.1016/j.compstruc.2014.03.007 – volume: 37 start-page: 1676 issue: 2 year: 2010 ident: 10.1016/j.cma.2021.114194_b94 article-title: Gaussian quantum-behaved particle swarm optimization approaches for constrained engineering design problems publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2009.06.044 – start-page: 276 year: 2019 ident: 10.1016/j.cma.2021.114194_b9 article-title: A sensitivity analysis for harmony search with multi-parent crossover algorithm – volume: 59 start-page: 53 year: 2013 ident: 10.1016/j.cma.2021.114194_b34 article-title: A new optimization method: Dolphin echolocation publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2013.03.004 – volume: 333 start-page: 356 year: 2018 ident: 10.1016/j.cma.2021.114194_b80 article-title: Stress-based topology optimization using bi-directional evolutionary structural optimization method publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/j.cma.2018.01.035 – volume: 186 start-page: 1407 issue: 2 year: 2007 ident: 10.1016/j.cma.2021.114194_b93 article-title: A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization publication-title: Appl. Math. Comput. – volume: 163 start-page: 283 year: 2019 ident: 10.1016/j.cma.2021.114194_b5 article-title: Atom search optimization and its application to solve a hydrogeologic parameter estimation problem publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2018.08.030 – volume: 205 start-page: 2325 issue: 16 year: 2002 ident: 10.1016/j.cma.2021.114194_b60 article-title: The ecological and evolutionary interface of hummingbird flight physiology publication-title: J. Exp. Biol. doi: 10.1242/jeb.205.16.2325 – volume: 5 start-page: 1052 issue: 8 year: 2016 ident: 10.1016/j.cma.2021.114194_b66 article-title: Outperforming hummingbirds’ load-lifting capability with a lightweight hummingbird-like flapping-wing mechanism publication-title: Biol. Open doi: 10.1242/bio.014357 – volume: 270 start-page: 1271 issue: 1521 year: 2003 ident: 10.1016/j.cma.2021.114194_b62 article-title: Context–dependent foraging decisions in rufous hummingbirds publication-title: Proc. R. Soc. B doi: 10.1098/rspb.2003.2365 – volume: 69 start-page: 46 year: 2014 ident: 10.1016/j.cma.2021.114194_b51 article-title: Grey wolf optimizer publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2013.12.007 – volume: 5 start-page: 315 issue: 3 year: 2005 ident: 10.1016/j.cma.2021.114194_b3 article-title: Evolutionary software engineering, a review publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2004.08.004 – volume: 11 start-page: 341 issue: 4 year: 1997 ident: 10.1016/j.cma.2021.114194_b67 article-title: Differential evolution–A simple and efficient heuristic for global optimization over continuous spaces publication-title: J. Global Optim. doi: 10.1023/A:1008202821328 – volume: 267 start-page: 66 issue: 1 year: 1992 ident: 10.1016/j.cma.2021.114194_b16 article-title: Genetic algorithms publication-title: Sci. Am. doi: 10.1038/scientificamerican0792-66 – year: 2013 ident: 10.1016/j.cma.2021.114194_b52 – volume: 13 start-page: 68 year: 2016 ident: 10.1016/j.cma.2021.114194_b110 article-title: A cooperative particle swarm optimizer with stochastic movements for computationally expensive numerical optimization problems publication-title: J. Comput. Sci. doi: 10.1016/j.jocs.2016.01.004 – volume: 114 start-page: 48 year: 2017 ident: 10.1016/j.cma.2021.114194_b42 article-title: Spotted hyena optimizer: a novel bio-inspired based metaheuristic technique for engineering applications publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2017.05.014 – volume: 36 start-page: 585 issue: 5 year: 2004 ident: 10.1016/j.cma.2021.114194_b106 article-title: An improved particle swarm optimizer for mechanical design optimization problems publication-title: Eng. Optim. doi: 10.1080/03052150410001704854 – volume: 26 start-page: 69 year: 2012 ident: 10.1016/j.cma.2021.114194_b30 article-title: A new fruit fly optimization algorithm: taking the financial distress model as an example publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2011.07.001 – start-page: 582 year: 2005 ident: 10.1016/j.cma.2021.114194_b95 article-title: Unified particle swarm optimization for solving constrained engineering optimization problems – volume: 47 start-page: 1059 issue: 4 year: 2017 ident: 10.1016/j.cma.2021.114194_b15 article-title: A hybrid bio-inspired algorithm and its application publication-title: Appl. Intell. doi: 10.1007/s10489-017-0951-y – volume: 1 start-page: 67 issue: 1 year: 1997 ident: 10.1016/j.cma.2021.114194_b54 article-title: No free lunch theorems for optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.585893 – volume: 1 start-page: 3 issue: 1 year: 2011 ident: 10.1016/j.cma.2021.114194_b72 article-title: A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2011.02.002 – start-page: 490 year: 2013 ident: 10.1016/j.cma.2021.114194_b75 – volume: 372 year: 2020 ident: 10.1016/j.cma.2021.114194_b10 article-title: An optimization algorithm for automatic structural design publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/j.cma.2020.113335 – volume: 10 issue: 5 year: 2015 ident: 10.1016/j.cma.2021.114194_b21 article-title: A comprehensive review of swarm optimization algorithms publication-title: PLoS One – volume: 36 start-page: 219 issue: 2 year: 2004 ident: 10.1016/j.cma.2021.114194_b91 article-title: Efficient evolutionary optimization through the use of a cultural algorithm publication-title: Eng. Optim. doi: 10.1080/03052150410001647966 – volume: 116 start-page: 405 year: 1994 ident: 10.1016/j.cma.2021.114194_b107 article-title: An augmented Lagrange multiplier based method for mixed integer discrete continuous optimization and its applications to mechanical design publication-title: J. Mech. Des. doi: 10.1115/1.2919393 – volume: 33 start-page: 292 year: 2015 ident: 10.1016/j.cma.2021.114194_b45 article-title: The runner-root algorithm: A metaheuristic for solving unimodal and multimodal optimization problems inspired by runners and roots of plants in nature publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.04.048 – volume: 29 start-page: 464 issue: 5 year: 2012 ident: 10.1016/j.cma.2021.114194_b28 article-title: Bat algorithm: a novel approach for global engineering optimization publication-title: Eng. Comput. doi: 10.1108/02644401211235834 – volume: 97 start-page: 1227 issue: 2 year: 2019 ident: 10.1016/j.cma.2021.114194_b58 article-title: Hummingbirds optimization algorithm-based particle filter for maneuvering target tracking publication-title: Nonlinear Dynam. doi: 10.1007/s11071-019-05043-0 – volume: 32 start-page: 675 issue: 200 year: 1937 ident: 10.1016/j.cma.2021.114194_b73 article-title: The use of ranks to avoid the assumption of normality implicit in the analysis of variance publication-title: J. Amer. Statist. Assoc. doi: 10.1080/01621459.1937.10503522 – volume: 41 start-page: 113 issue: 2 year: 2000 ident: 10.1016/j.cma.2021.114194_b89 article-title: Use of a self-adaptive penalty approach for engineering optimization problems publication-title: Comput. Ind. doi: 10.1016/S0166-3615(99)00046-9 – volume: 67 start-page: 246 year: 2018 ident: 10.1016/j.cma.2021.114194_b53 article-title: Optimization of neural network using kidney-inspired algorithm with control of filtration rate and chaotic map for real-world rainfall forecasting publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2017.09.012 – volume: 186 start-page: 340 issue: 1 year: 2007 ident: 10.1016/j.cma.2021.114194_b96 article-title: An effective co-evolutionary differential evolution for constrained optimization publication-title: Appl. Math. Comput. – volume: 87 year: 2020 ident: 10.1016/j.cma.2021.114194_b81 article-title: Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2019.103300 – volume: 159 start-page: 20 year: 2018 ident: 10.1016/j.cma.2021.114194_b39 article-title: Emperor penguin optimizer: A bio-inspired algorithm for engineering problems publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2018.06.001 – volume: 43 start-page: 303 issue: 3 year: 2011 ident: 10.1016/j.cma.2021.114194_b100 article-title: Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems publication-title: Comput. Aided Des. doi: 10.1016/j.cad.2010.12.015 – volume: 155 year: 2020 ident: 10.1016/j.cma.2021.114194_b8 article-title: An efficient Harris hawks-inspired image segmentation method publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2020.113428 – volume: 53 start-page: 113 year: 2013 ident: 10.1016/j.cma.2021.114194_b68 article-title: Energy and spinning reserve scheduling for a wind-thermal power system using CMA-ES with mean learning technique publication-title: Int. J. Electr. Power Energy Syst. doi: 10.1016/j.ijepes.2013.03.032 – ident: 10.1016/j.cma.2021.114194_b112 – start-page: 210 year: 2009 ident: 10.1016/j.cma.2021.114194_b24 article-title: Cuckoo search via Lévy flights – volume: 1 start-page: 330 issue: 4 year: 2010 ident: 10.1016/j.cma.2021.114194_b25 article-title: Engineering optimisation by cuckoo search publication-title: Int. J. Math. Model. Numer. Optim. – volume: 197 start-page: 3080 issue: 33–40 year: 2008 ident: 10.1016/j.cma.2021.114194_b76 article-title: Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/j.cma.2008.02.006 – volume: 35 start-page: 268 year: 2003 ident: 10.1016/j.cma.2021.114194_b2 article-title: Meta-heuristics in combinatorial optimization: Overview and conceptual comparison publication-title: ACM Comput. Surv. doi: 10.1145/937503.937505 – volume: 97 start-page: 144 year: 2016 ident: 10.1016/j.cma.2021.114194_b50 article-title: Monkey king evolution: A new memetic evolutionary algorithm and its application in vehicle fuel consumption optimization publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2016.01.009 – volume: 72 start-page: 393 year: 2018 ident: 10.1016/j.cma.2021.114194_b38 article-title: Tree growth algorithm (TGA): A novel approach for solving optimization problems publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2018.04.021 – start-page: 71 year: 2013 ident: 10.1016/j.cma.2021.114194_b69 article-title: Success-history based parameter adaptation for differential evolution – volume: 8 start-page: 657 issue: 4 year: 2012 ident: 10.1016/j.cma.2021.114194_b61 article-title: Hummingbirds have a greatly enlarged hippocampal formation publication-title: Biol. Lett. doi: 10.1098/rsbl.2011.1180 – volume: 88 year: 2020 ident: 10.1016/j.cma.2021.114194_b99 article-title: Performance analysis of chaotic multi-verse harris hawks optimization: a case study on solving engineering problems publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2019.103370 – volume: 1 start-page: 355 issue: 4 year: 2006 ident: 10.1016/j.cma.2021.114194_b40 article-title: A novel numerical optimization algorithm inspired from weed colonization publication-title: Ecol. Inform. doi: 10.1016/j.ecoinf.2006.07.003 – volume: 3 start-page: 231 issue: 2 year: 2018 ident: 10.1016/j.cma.2021.114194_b14 article-title: Bio-inspired computing: Algorithms review, deep analysis, and the scope of applications publication-title: Future Comput. Inform. J. doi: 10.1016/j.fcij.2018.06.001 – volume: 17 start-page: 4831 issue: 12 year: 2012 ident: 10.1016/j.cma.2021.114194_b43 article-title: Krill herd: A new bio-inspired optimization algorithm publication-title: Commun. Nonlinear Sci. Numer. Simul. doi: 10.1016/j.cnsns.2012.05.010 – volume: 8 start-page: 1204 issue: 5 year: 2021 ident: 10.1016/j.cma.2021.114194_b12 article-title: An adaptive hybrid atom search optimization with particle swarm optimization and its application to optimal no-load PID design of hydro-turbine governor publication-title: J. comput. Des. Eng. – volume: 20 start-page: 89 issue: 1 year: 2007 ident: 10.1016/j.cma.2021.114194_b92 article-title: An effective co-evolutionary particle swarm optimization for constrained engineering design problems publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2006.03.003 – start-page: 240 year: 2012 ident: 10.1016/j.cma.2021.114194_b48 article-title: Flower pollination algorithm for global optimization – volume: 376 year: 2021 ident: 10.1016/j.cma.2021.114194_b11 article-title: The arithmetic optimization algorithm publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/j.cma.2020.113609 – volume: 339 start-page: 341 year: 2018 ident: 10.1016/j.cma.2021.114194_b13 article-title: An adaptive multiscale approach for identifying multiple flaws based on XFEM and a discrete artificial fish swarm algorithm publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/j.cma.2018.04.037 – volume: 36 start-page: 3880 issue: 2 year: 2009 ident: 10.1016/j.cma.2021.114194_b108 article-title: Hybrid Nelder–Mead simplex search and particle swarm optimization for constrained engineering design problems publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2008.02.039 – volume: 8 start-page: 74 issue: 1 year: 2012 ident: 10.1016/j.cma.2021.114194_b59 article-title: Observations from the jewel rooms publication-title: Ecotone doi: 10.1353/ect.2012.0064 – volume: 31 start-page: 1118 issue: 6 year: 2011 ident: 10.1016/j.cma.2021.114194_b117 article-title: Optimal operation of cascade reservoirs based on improved artificial fish swarm algorithm publication-title: Syst. Eng. Theory Pract. – volume: 29 start-page: 17 issue: 1 year: 2013 ident: 10.1016/j.cma.2021.114194_b85 article-title: Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems publication-title: Eng. Comput. doi: 10.1007/s00366-011-0241-y – volume: 217 start-page: 3166 issue: 7 year: 2010 ident: 10.1016/j.cma.2021.114194_b55 article-title: Gbest-guided artificial bee colony algorithm for numerical function optimization publication-title: Appl. Math. Comput. – volume: 110 start-page: 151 year: 2012 ident: 10.1016/j.cma.2021.114194_b111 article-title: Water cycle algorithm–A novel metaheuristic optimization method for solving constrained engineering optimization problems publication-title: Comput. Struct. doi: 10.1016/j.compstruc.2012.07.010 – start-page: 1942 year: 1995 ident: 10.1016/j.cma.2021.114194_b18 article-title: Particle swarm optimization – volume: 105 start-page: 30 year: 2017 ident: 10.1016/j.cma.2021.114194_b47 article-title: Grasshopper optimisation algorithm: theory and application publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2017.01.004 – volume: 33 start-page: 482 issue: 2 year: 1962 ident: 10.1016/j.cma.2021.114194_b74 article-title: Rank methods for combination of independent experiments in analysis of variance publication-title: Ann. Math. Stat. doi: 10.1214/aoms/1177704575 – volume: 194 start-page: 3902 issue: 36–38 year: 2005 ident: 10.1016/j.cma.2021.114194_b109 article-title: A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/j.cma.2004.09.007 – volume: 22 start-page: R472 issue: 12 year: 2012 ident: 10.1016/j.cma.2021.114194_b65 article-title: Hummingbird flight publication-title: Curr. Biol. doi: 10.1016/j.cub.2012.04.057 – volume: 19 start-page: 1213 issue: 4 year: 2014 ident: 10.1016/j.cma.2021.114194_b46 article-title: Bird mating optimizer: an optimization algorithm inspired by bird mating strategies publication-title: Commun. Nonlinear Sci. Numer. Simul. doi: 10.1016/j.cnsns.2013.08.027 – year: 2002 ident: 10.1016/j.cma.2021.114194_b113 – volume: 12 start-page: 1809 issue: 6 year: 2016 ident: 10.1016/j.cma.2021.114194_b26 article-title: Cuckoo search algorithm based on mobile cloud model publication-title: Int. J. Innovative Comput. Inf. Control – volume: 7 start-page: 73182 year: 2019 ident: 10.1016/j.cma.2021.114194_b7 article-title: Supply-demand-based optimization: a novel economics-inspired algorithm for global optimization publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2918753 – start-page: 521 year: 1997 ident: 10.1016/j.cma.2021.114194_b104 article-title: Optimizing engineering designs using a combined genetic search – year: 2020 ident: 10.1016/j.cma.2021.114194_b118 article-title: Optimal hydropower station dispatch using quantum social spider optimization algorithm publication-title: Concurr. Comput.: Pract. Exper. – volume: 2 start-page: 27 issue: 1 year: 2004 ident: 10.1016/j.cma.2021.114194_b71 article-title: Global optima for linearly constrained business decision models publication-title: Sci. J. Adm. – volume: 44 start-page: 148 year: 2019 ident: 10.1016/j.cma.2021.114194_b32 article-title: A novel nature-inspired algorithm for optimization: Squirrel search algorithm publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2018.02.013 – volume: 214 start-page: 108 issue: 1 year: 2009 ident: 10.1016/j.cma.2021.114194_b22 article-title: A comparative study of artificial bee colony algorithm publication-title: Appl. Math. Comput. – start-page: 1 year: 2016 ident: 10.1016/j.cma.2021.114194_b27 article-title: An improved cuckoo search optimization algorithm for the problem of chaotic systems parameter estimation publication-title: Comput. Intell. Neurosci. – year: 1982 ident: 10.1016/j.cma.2021.114194_b105 – volume: 7 start-page: 3309 issue: 9 year: 2011 ident: 10.1016/j.cma.2021.114194_b23 article-title: An effective refinement artificial bee colony optimization algorithm based on chaotic search and application for PID control tuning publication-title: J. Comput. Inf Syst. – volume: 21 start-page: 97 issue: 5 year: 2016 ident: 10.1016/j.cma.2021.114194_b35 article-title: A new metaheuristic algorithm based on shark smell optimization publication-title: Complexity doi: 10.1002/cplx.21634 – volume: 10 start-page: 629 issue: 2 year: 2010 ident: 10.1016/j.cma.2021.114194_b83 article-title: Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2009.08.031 – volume: 2015 year: 2015 ident: 10.1016/j.cma.2021.114194_b19 article-title: A comprehensive survey on particle swarm optimization algorithm and its applications publication-title: Math. Probl. Eng. – volume: 93 year: 2020 ident: 10.1016/j.cma.2021.114194_b57 article-title: A memory-based grey wolf optimizer for global optimization tasks publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.106367 – volume: 185 start-page: 17 year: 2021 ident: 10.1016/j.cma.2021.114194_b56 article-title: Nature-inspired approach: An enhanced whale optimization algorithm for global optimization publication-title: Math. Comput. Simulation doi: 10.1016/j.matcom.2020.12.008 – volume: 13 start-page: 2592 issue: 5 year: 2013 ident: 10.1016/j.cma.2021.114194_b101 article-title: Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2012.11.026 – volume: 97 start-page: 849 year: 2019 ident: 10.1016/j.cma.2021.114194_b78 article-title: Harris hawks optimization: Algorithm and applications publication-title: Future Gener. Comput. Syst. doi: 10.1016/j.future.2019.02.028 – start-page: 652 year: 2005 ident: 10.1016/j.cma.2021.114194_b97 article-title: Useful infeasible solutions in engineering optimization with evolutionary algorithms – volume: 23 start-page: 715 issue: 3 year: 2019 ident: 10.1016/j.cma.2021.114194_b41 article-title: Butterfly optimization algorithm: a novel approach for global optimization publication-title: Soft Comput. doi: 10.1007/s00500-018-3102-4 – volume: 60 start-page: 1 year: 2017 ident: 10.1016/j.cma.2021.114194_b44 article-title: Satin bowerbird optimizer: A new optimization algorithm to optimize ANFIS for software development effort estimation publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2017.01.006 – volume: 26 start-page: 29 issue: 1 year: 1996 ident: 10.1016/j.cma.2021.114194_b20 article-title: Ant system: optimization by a colony of cooperating agents publication-title: IEEE Trans. Syst. Man Cybern. B doi: 10.1109/3477.484436 – volume: 40 start-page: 3951 issue: 5–6 year: 2016 ident: 10.1016/j.cma.2021.114194_b77 article-title: Passing vehicle search (PVS): A novel metaheuristic algorithm publication-title: Appl. Math. Model. doi: 10.1016/j.apm.2015.10.040 – volume: 191 start-page: 1245 issue: 11–12 year: 2002 ident: 10.1016/j.cma.2021.114194_b79 article-title: Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/S0045-7825(01)00323-1 |
| SSID | ssj0000812 |
| Score | 2.7429178 |
| Snippet | A new bio-inspired optimization algorithm called artificial hummingbird algorithm (AHA) is proposed in this work to solve optimization problems. The AHA... |
| SourceID | proquest crossref elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 114194 |
| SubjectTerms | Algorithm Algorithms Artificial hummingbird algorithm Benchmark Bio-inspired computing Design engineering Engineering optimization Foraging behavior Genetic algorithm Heuristic methods Meta-heuristics Optimization Optimization techniques Skills Source code Swarm intelligence |
| Title | Artificial hummingbird algorithm: A new bio-inspired optimizer with its engineering applications |
| URI | https://dx.doi.org/10.1016/j.cma.2021.114194 https://www.proquest.com/docview/2622813538 |
| Volume | 388 |
| WOSCitedRecordID | wos000720455700009&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: ScienceDirect Freedom Collection - Elsevier customDbUrl: eissn: 1879-2138 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000812 issn: 0045-7825 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwELfKxgM88DGYGAzkB8QDVVBi58PhrUKdAJWCRDf6ZmLH3VJ1aUm7aeOVf5xz7DSmggoekKqoSfNR-X45_-7Od4fQ85jG8SQQiSeAy3rA_5WXyUB5REQ0onmWp3XE9GSQDIdsPE4_dTo_mlyYy1lSluzqKl38V1HDMRC2Tp39B3GvbwoH4DsIHbYgdtj-leB7Vb38R3vCz-CxMDWJosq72ex0XhWrM-OY153Eu6KYe0WpQ-3AOuegO86L76oyrlkdT1BtrcKuG-h2CW3TFcK2oq5X12aW2Z4rnVbclIF27uZ4q2tP7RdVnF7MW9--0T-D4to590NRTcFmMNncn9W1ymHP9VkQsuGzaJNpTlzdHEYe8JXI1c3U9Pyz2jX4rc437ofpK1nXkSKBLn8cmM7Jv9bXHn7kR8eDAR_1x6MXi2-ebj2mQ_S2D8sNtEuSKAXVuNt71x-_byd0Fpii8_YPNsHxepngxlP_RG82JvqavYzuoTvW7MA9A5f7qKPKPXTXmiDYKvjlHrrt1Kd8gL62WMIOlvAaS69xDwOSsIskvEYS1kjCgCTsyB67SHqIjo_6ozdvPduSw5M0ZitPRDJhMhFEyEikPpWC-MBYaZYomocqCBWYD4GfhpM8kZnMUqbD1HnuR5KSScLoPtop56V6hDAw0cjPYMYIc_iElIWBoGEUTsBmz2KRHCC_GUkubb163TZlxpuFiVMOg8_14HMz-Afo5fqShSnWsu3ksBEPt2zTsEgOwNp22WEjSm7f-iUnMSFMd5Bhj7f__ATdat-HQ7Szqi7UU3RTXq6KZfXMAu8nDuCrLw |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Artificial+hummingbird+algorithm%3A+A+new+bio-inspired+optimizer+with+its+engineering+applications&rft.jtitle=Computer+methods+in+applied+mechanics+and+engineering&rft.au=Zhao%2C+Weiguo&rft.au=Wang%2C+Liying&rft.au=Mirjalili%2C+Seyedali&rft.date=2022-01-01&rft.pub=Elsevier+BV&rft.issn=0045-7825&rft.volume=388&rft.spage=1&rft_id=info:doi/10.1016%2Fj.cma.2021.114194&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0045-7825&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0045-7825&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0045-7825&client=summon |