Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems

The difficulty and complexity of the real-world numerical optimization problems has grown manifold, which demands efficient optimization methods. To date, various metaheuristic approaches have been introduced, but only a few have earned recognition in research community. In this paper, a new metaheu...

Full description

Saved in:

Bibliographic Details
Published in:	Applied intelligence (Dordrecht, Netherlands) Vol. 51; no. 3; pp. 1531 - 1551
Main Authors:	Hashim, Fatma A., Hussain, Kashif, Houssein, Essam H., Mabrouk, Mai S., Al-Atabany, Walid
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.03.2021 Springer Nature B.V
Subjects:	Artificial Intelligence Complexity Computer Science Design engineering Evolutionary computation Genetic algorithms Heuristic methods Machines Manufacturing Mechanical Engineering Optimization algorithms Particle swarm optimization Performance evaluation Processes Software testing Source code Trigonometric functions Exploration and exploitation Buoyant force Metaheuristic Archimedes’ principle Optimization
ISSN:	0924-669X, 1573-7497
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	The difficulty and complexity of the real-world numerical optimization problems has grown manifold, which demands efficient optimization methods. To date, various metaheuristic approaches have been introduced, but only a few have earned recognition in research community. In this paper, a new metaheuristic algorithm called Archimedes optimization algorithm (AOA) is introduced to solve the optimization problems. AOA is devised with inspirations from an interesting law of physics Archimedes’ Principle. It imitates the principle of buoyant force exerted upward on an object, partially or fully immersed in fluid, is proportional to weight of the displaced fluid. To evaluate performance, the proposed AOA algorithm is tested on CEC’17 test suite and four engineering design problems. The solutions obtained with AOA have outperformed well-known state-of-the-art and recently introduced metaheuristic algorithms such genetic algorithms (GA), particle swarm optimization (PSO), differential evolution variants L-SHADE and LSHADE-EpSin, whale optimization algorithm (WOA), sine-cosine algorithm (SCA), Harris’ hawk optimization (HHO), and equilibrium optimizer (EO). The experimental results suggest that AOA is a high-performance optimization tool with respect to convergence speed and exploration-exploitation balance, as it is effectively applicable for solving complex problems. The source code is currently available for public from: https://www.mathworks.com/matlabcentral/fileexchange/79822-archimedes-optimization-algorithm
AbstractList	The difficulty and complexity of the real-world numerical optimization problems has grown manifold, which demands efficient optimization methods. To date, various metaheuristic approaches have been introduced, but only a few have earned recognition in research community. In this paper, a new metaheuristic algorithm called Archimedes optimization algorithm (AOA) is introduced to solve the optimization problems. AOA is devised with inspirations from an interesting law of physics Archimedes’ Principle. It imitates the principle of buoyant force exerted upward on an object, partially or fully immersed in fluid, is proportional to weight of the displaced fluid. To evaluate performance, the proposed AOA algorithm is tested on CEC’17 test suite and four engineering design problems. The solutions obtained with AOA have outperformed well-known state-of-the-art and recently introduced metaheuristic algorithms such genetic algorithms (GA), particle swarm optimization (PSO), differential evolution variants L-SHADE and LSHADE-EpSin, whale optimization algorithm (WOA), sine-cosine algorithm (SCA), Harris’ hawk optimization (HHO), and equilibrium optimizer (EO). The experimental results suggest that AOA is a high-performance optimization tool with respect to convergence speed and exploration-exploitation balance, as it is effectively applicable for solving complex problems. The source code is currently available for public from: https://www.mathworks.com/matlabcentral/fileexchange/79822-archimedes-optimization-algorithm The difficulty and complexity of the real-world numerical optimization problems has grown manifold, which demands efficient optimization methods. To date, various metaheuristic approaches have been introduced, but only a few have earned recognition in research community. In this paper, a new metaheuristic algorithm called Archimedes optimization algorithm (AOA) is introduced to solve the optimization problems. AOA is devised with inspirations from an interesting law of physics Archimedes’ Principle. It imitates the principle of buoyant force exerted upward on an object, partially or fully immersed in fluid, is proportional to weight of the displaced fluid. To evaluate performance, the proposed AOA algorithm is tested on CEC’17 test suite and four engineering design problems. The solutions obtained with AOA have outperformed well-known state-of-the-art and recently introduced metaheuristic algorithms such genetic algorithms (GA), particle swarm optimization (PSO), differential evolution variants L-SHADE and LSHADE-EpSin, whale optimization algorithm (WOA), sine-cosine algorithm (SCA), Harris’ hawk optimization (HHO), and equilibrium optimizer (EO). The experimental results suggest that AOA is a high-performance optimization tool with respect to convergence speed and exploration-exploitation balance, as it is effectively applicable for solving complex problems. The source code is currently available for public from: https://www.mathworks.com/matlabcentral/fileexchange/79822-archimedes-optimization-algorithm
Author	Mabrouk, Mai S. Hashim, Fatma A. Hussain, Kashif Houssein, Essam H. Al-Atabany, Walid
Author_xml	– sequence: 1 givenname: Fatma A. surname: Hashim fullname: Hashim, Fatma A. organization: Faculty of Engineering, Helwan University – sequence: 2 givenname: Kashif surname: Hussain fullname: Hussain, Kashif organization: Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China – sequence: 3 givenname: Essam H. orcidid: 0000-0002-8127-7233 surname: Houssein fullname: Houssein, Essam H. email: essam.halim@mu.edu.eg organization: Faculty of Computers and Information, Minia University – sequence: 4 givenname: Mai S. surname: Mabrouk fullname: Mabrouk, Mai S. organization: Faculty of Engineering, Misr University for Science and Technology – sequence: 5 givenname: Walid surname: Al-Atabany fullname: Al-Atabany, Walid organization: Faculty of Engineering, Helwan University
BookMark	eNp9kM9LwzAcxYNMcJv-A54KnqvfNG2TeBvDXzDwouAtJGm6ZbTNTDLF_fXWVRh62Ol7-L7Pe483QaPOdQahSwzXGIDeBAw54ylkkAJmnKS7EzTGBSUpzTkdoTHwLE_Lkr-doUkIawAgBPAYqZnXK9uayoTEbaJt7U5G67pENkvnbVy1t4lMOvOZtCbKldl6G6LVh3dSO58E13zYbvnXYeOdakwbztFpLZtgLn7vFL3e373MH9PF88PTfLZINWFFTBnDWV6VlGdaGUlAa6OgyKRUlBVMQWWI4jWUOZVVgTmrGKU11DVlSnPGSzJFV4NvH_y-NSGKtdv6ro8UWc5oSYBg3qvYoNLeheBNLbSN-8LRS9sIDOJnUTEsKvpFxX5RsevR7B-68baV_us4RAYo9OJuafyh1RHqG2hnjmo
CitedBy_id	crossref_primary_10_1016_j_ast_2023_108541 crossref_primary_10_1016_j_knosys_2022_108457 crossref_primary_10_32604_cmc_2024_053189 crossref_primary_10_1007_s10462_022_10340_z crossref_primary_10_1007_s10586_024_04620_2 crossref_primary_10_32604_cmc_2023_034025 crossref_primary_10_3390_pr11051502 crossref_primary_10_1016_j_nexus_2025_100500 crossref_primary_10_1016_j_matcom_2025_04_003 crossref_primary_10_1016_j_dajour_2023_100361 crossref_primary_10_1016_j_asoc_2025_112854 crossref_primary_10_1016_j_enconman_2023_116907 crossref_primary_10_3390_pr12020406 crossref_primary_10_1016_j_asoc_2025_113943 crossref_primary_10_1016_j_cma_2022_115676 crossref_primary_10_1007_s10586_024_04654_6 crossref_primary_10_1002_dac_5604 crossref_primary_10_3390_info16030207 crossref_primary_10_1002_int_23091 crossref_primary_10_1088_1402_4896_adbfd6 crossref_primary_10_1016_j_bspc_2023_105870 crossref_primary_10_1016_j_matcom_2022_06_027 crossref_primary_10_1016_j_jclepro_2022_132709 crossref_primary_10_1002_dac_70216 crossref_primary_10_1016_j_eswa_2023_122937 crossref_primary_10_1371_journal_pone_0280006 crossref_primary_10_1016_j_compeleceng_2022_108014 crossref_primary_10_1016_j_advengsoft_2023_103517 crossref_primary_10_1016_j_epsr_2023_109970 crossref_primary_10_3390_buildings14113695 crossref_primary_10_1016_j_enbuild_2024_114690 crossref_primary_10_33889_IJMEMS_2025_10_4_051 crossref_primary_10_1016_j_egyr_2021_10_117 crossref_primary_10_1016_j_asoc_2022_108538 crossref_primary_10_1109_ACCESS_2025_3562367 crossref_primary_10_1177_18758967251360039 crossref_primary_10_1007_s00521_023_08492_2 crossref_primary_10_1016_j_est_2022_104591 crossref_primary_10_1016_j_compbiomed_2024_108329 crossref_primary_10_1007_s00521_023_08769_6 crossref_primary_10_1109_ACCESS_2023_3311271 crossref_primary_10_1007_s40996_024_01710_4 crossref_primary_10_1007_s10586_024_04328_3 crossref_primary_10_1007_s11053_025_10546_2 crossref_primary_10_1016_j_chaos_2024_115696 crossref_primary_10_1016_j_eswa_2023_120602 crossref_primary_10_1016_j_knosys_2021_108071 crossref_primary_10_1080_15567036_2023_2186539 crossref_primary_10_1016_j_chaos_2024_115578 crossref_primary_10_52254_1857_0070_2024_1_61_01 crossref_primary_10_1007_s41939_023_00318_x crossref_primary_10_1109_ACCESS_2024_3470845 crossref_primary_10_1016_j_jobe_2023_106922 crossref_primary_10_1007_s00366_021_01591_5 crossref_primary_10_1007_s10586_024_04447_x crossref_primary_10_1016_j_ins_2022_06_008 crossref_primary_10_1007_s11227_024_05905_4 crossref_primary_10_1186_s42490_025_00098_0 crossref_primary_10_1016_j_future_2022_12_040 crossref_primary_10_1007_s00521_023_08649_z crossref_primary_10_3390_electronics12041058 crossref_primary_10_1016_j_engappai_2021_104417 crossref_primary_10_1007_s10489_023_04962_1 crossref_primary_10_1007_s11042_023_17327_0 crossref_primary_10_1007_s11277_024_11287_w crossref_primary_10_1016_j_measurement_2022_110798 crossref_primary_10_1016_j_asoc_2024_111581 crossref_primary_10_1007_s12530_022_09443_3 crossref_primary_10_1007_s40313_023_01033_1 crossref_primary_10_3390_e24081018 crossref_primary_10_52254_1857_0070_2023_4_60_02 crossref_primary_10_1016_j_aeue_2025_155986 crossref_primary_10_1016_j_ijleo_2022_169692 crossref_primary_10_1016_j_knosys_2025_113548 crossref_primary_10_1016_j_compgeo_2024_106618 crossref_primary_10_3390_jcs8060205 crossref_primary_10_1007_s42235_024_00505_7 crossref_primary_10_1007_s10489_022_03586_1 crossref_primary_10_1016_j_compbiomed_2023_107197 crossref_primary_10_1007_s40998_023_00675_w crossref_primary_10_3390_pr10020366 crossref_primary_10_17482_uumfd_1090766 crossref_primary_10_1016_j_compeleceng_2025_110270 crossref_primary_10_1007_s11770_023_1010_6 crossref_primary_10_3390_biomimetics10090628 crossref_primary_10_1007_s40313_022_00909_y crossref_primary_10_1007_s12065_024_00937_4 crossref_primary_10_1007_s11831_025_10228_5 crossref_primary_10_13005_bpj_3052 crossref_primary_10_3390_en17225552 crossref_primary_10_1109_ACCESS_2023_3283422 crossref_primary_10_1007_s11831_023_09990_1 crossref_primary_10_1007_s00521_022_07530_9 crossref_primary_10_1016_j_compbiomed_2024_108353 crossref_primary_10_12677_mos_2025_141003 crossref_primary_10_1016_j_knosys_2023_110722 crossref_primary_10_1007_s11831_025_10281_0 crossref_primary_10_3390_a15090317 crossref_primary_10_3390_app14114878 crossref_primary_10_1038_s41598_023_31876_2 crossref_primary_10_36548_jaicn_2025_2_001 crossref_primary_10_3390_biomimetics10090638 crossref_primary_10_1016_j_knosys_2022_108124 crossref_primary_10_1038_s41598_023_48479_6 crossref_primary_10_1038_s41598_025_12581_8 crossref_primary_10_3390_en16052409 crossref_primary_10_1002_er_8114 crossref_primary_10_1080_21642583_2024_2385310 crossref_primary_10_1038_s41598_025_90178_x crossref_primary_10_1007_s11831_023_09902_3 crossref_primary_10_1016_j_ijhydene_2024_12_381 crossref_primary_10_3390_biomimetics8060470 crossref_primary_10_1016_j_jfranklin_2024_107398 crossref_primary_10_1016_j_engappai_2022_105075 crossref_primary_10_1016_j_energy_2022_123447 crossref_primary_10_1177_09544062241240395 crossref_primary_10_1155_2021_9931677 crossref_primary_10_3390_biomimetics8010121 crossref_primary_10_3390_su14010310 crossref_primary_10_1016_j_apenergy_2021_117449 crossref_primary_10_1007_s10098_022_02334_w crossref_primary_10_3390_math10142396 crossref_primary_10_3389_fmech_2022_1126450 crossref_primary_10_1016_j_bspc_2023_105423 crossref_primary_10_1016_j_eswa_2022_119015 crossref_primary_10_1177_18724981251322925 crossref_primary_10_1016_j_jocs_2024_102323 crossref_primary_10_1016_j_matpr_2022_03_253 crossref_primary_10_3390_su142114287 crossref_primary_10_1007_s00371_021_02285_1 crossref_primary_10_1007_s00521_023_09064_0 crossref_primary_10_1016_j_bspc_2023_105419 crossref_primary_10_1017_S0263574725000049 crossref_primary_10_1016_j_eswa_2023_122705 crossref_primary_10_1016_j_asoc_2021_108387 crossref_primary_10_1049_cth2_12277 crossref_primary_10_1016_j_istruc_2023_04_102 crossref_primary_10_3390_biomimetics8020162 crossref_primary_10_1007_s10489_024_05804_4 crossref_primary_10_1007_s11063_023_11230_3 crossref_primary_10_1109_ACCESS_2024_3455550 crossref_primary_10_3233_JIFS_221036 crossref_primary_10_3233_JIFS_221039 crossref_primary_10_1016_j_knosys_2023_110940 crossref_primary_10_1016_j_jhydrol_2022_129044 crossref_primary_10_1007_s00521_022_08103_6 crossref_primary_10_3390_en17184742 crossref_primary_10_32604_cmes_2023_025908 crossref_primary_10_1007_s00521_024_09497_1 crossref_primary_10_1007_s12065_025_01069_z crossref_primary_10_1016_j_ijepes_2025_110676 crossref_primary_10_1016_j_knosys_2025_113589 crossref_primary_10_1016_j_eswa_2023_121744 crossref_primary_10_1515_mt_2024_0151 crossref_primary_10_1007_s12530_024_09645_x crossref_primary_10_1016_j_eswa_2023_122830 crossref_primary_10_1007_s00521_024_10577_5 crossref_primary_10_1007_s10878_025_01304_4 crossref_primary_10_1016_j_jestch_2025_101982 crossref_primary_10_1038_s41598_024_70497_1 crossref_primary_10_1155_2022_1924906 crossref_primary_10_1016_j_dajour_2025_100608 crossref_primary_10_1016_j_knosys_2025_114430 crossref_primary_10_32604_cmes_2023_026231 crossref_primary_10_1080_21681163_2021_2024088 crossref_primary_10_1093_ijlct_ctae113 crossref_primary_10_3390_app12178749 crossref_primary_10_1007_s41870_022_01031_7 crossref_primary_10_3390_biomimetics8020149 crossref_primary_10_1007_s00202_024_02779_w crossref_primary_10_1007_s00500_023_08513_1 crossref_primary_10_1109_ACCESS_2022_3185737 crossref_primary_10_1155_2022_3082933 crossref_primary_10_1016_j_bspc_2022_104434 crossref_primary_10_1016_j_bspc_2023_104951 crossref_primary_10_1002_cpe_8393 crossref_primary_10_1007_s00521_022_07080_0 crossref_primary_10_3390_en15238884 crossref_primary_10_1109_ACCESS_2024_3365700 crossref_primary_10_1007_s11837_025_07625_3 crossref_primary_10_3390_modelling5030065 crossref_primary_10_1016_j_asoc_2023_110953 crossref_primary_10_1093_jcde_qwac113 crossref_primary_10_1002_int_22703 crossref_primary_10_1016_j_jestch_2023_101612 crossref_primary_10_1007_s10836_025_06157_7 crossref_primary_10_1016_j_bspc_2024_107395 crossref_primary_10_1016_j_est_2021_103035 crossref_primary_10_1155_jece_6682046 crossref_primary_10_1080_02286203_2025_2523064 crossref_primary_10_1109_JSEN_2022_3186063 crossref_primary_10_1007_s11227_022_04644_8 crossref_primary_10_1016_j_eswa_2021_115538 crossref_primary_10_1002_oca_3284 crossref_primary_10_1111_jph_13426 crossref_primary_10_1038_s41598_024_69010_5 crossref_primary_10_1007_s11227_025_07460_y crossref_primary_10_52254_1857_0070_2024_3_63_01 crossref_primary_10_1007_s12530_022_09425_5 crossref_primary_10_1109_ACCESS_2024_3376605 crossref_primary_10_1109_ACCESS_2024_3446239 crossref_primary_10_1016_j_eswa_2021_115651 crossref_primary_10_3390_fractalfract5040190 crossref_primary_10_1016_j_eswa_2023_120478 crossref_primary_10_7717_peerj_cs_1785 crossref_primary_10_1016_j_phycom_2025_102749 crossref_primary_10_1049_cth2_12441 crossref_primary_10_1109_ACCESS_2024_3495518 crossref_primary_10_1007_s10462_023_10516_1 crossref_primary_10_1016_j_knosys_2023_110774 crossref_primary_10_1016_j_eswa_2023_120594 crossref_primary_10_1007_s00034_025_03080_2 crossref_primary_10_1016_j_bspc_2025_107563 crossref_primary_10_3390_math13091432 crossref_primary_10_1080_15567036_2025_2488466 crossref_primary_10_1016_j_cie_2023_109502 crossref_primary_10_32604_cmes_2023_029404 crossref_primary_10_1016_j_egyr_2021_10_073 crossref_primary_10_1016_j_jappgeo_2025_105929 crossref_primary_10_1109_ACCESS_2023_3279416 crossref_primary_10_1002_ett_70057 crossref_primary_10_3390_s21134529 crossref_primary_10_3390_biomimetics8050383 crossref_primary_10_3390_biomimetics8020242 crossref_primary_10_3390_s23052764 crossref_primary_10_1007_s10462_023_10470_y crossref_primary_10_1038_s41598_022_27344_y crossref_primary_10_1016_j_eswa_2023_121898 crossref_primary_10_1007_s11227_023_05790_3 crossref_primary_10_32604_cmc_2022_025202 crossref_primary_10_3390_biomimetics8040332 crossref_primary_10_1016_j_matcom_2022_01_018 crossref_primary_10_1007_s00521_025_11421_0 crossref_primary_10_1007_s10462_024_10981_2 crossref_primary_10_1007_s00366_021_01470_z crossref_primary_10_1007_s10462_021_10100_5 crossref_primary_10_3390_math12162437 crossref_primary_10_1016_j_ecolind_2021_108285 crossref_primary_10_1016_j_engappai_2021_104372 crossref_primary_10_3390_s21155214 crossref_primary_10_1108_K_08_2023_1580 crossref_primary_10_1007_s11042_023_15129_y crossref_primary_10_1016_j_apenergy_2023_122054 crossref_primary_10_7717_peerj_cs_1526 crossref_primary_10_1007_s11277_023_10197_7 crossref_primary_10_1080_01430750_2023_2267569 crossref_primary_10_3390_math10152675 crossref_primary_10_1007_s00500_022_07668_7 crossref_primary_10_1016_j_measurement_2024_115373 crossref_primary_10_1007_s00500_022_07410_3 crossref_primary_10_1007_s13042_024_02488_7 crossref_primary_10_1016_j_jfranklin_2025_107910 crossref_primary_10_1007_s00500_024_10322_z crossref_primary_10_1007_s10489_022_03715_w crossref_primary_10_3390_biomimetics9030137 crossref_primary_10_1177_01423312211037967 crossref_primary_10_1007_s12145_024_01394_4 crossref_primary_10_1016_j_bspc_2024_106093 crossref_primary_10_1007_s12008_025_02311_9 crossref_primary_10_1038_s41598_025_01835_0 crossref_primary_10_1371_journal_pone_0291872 crossref_primary_10_1016_j_jer_2024_05_008 crossref_primary_10_1007_s44444_025_00008_8 crossref_primary_10_1038_s41598_024_59034_2 crossref_primary_10_3390_rs15215231 crossref_primary_10_1016_j_compbiomed_2022_105349 crossref_primary_10_1007_s10489_023_04732_z crossref_primary_10_1016_j_matcom_2022_02_030 crossref_primary_10_3233_JIFS_232114 crossref_primary_10_15407_techned2025_01_003 crossref_primary_10_1007_s42108_025_00344_0 crossref_primary_10_1038_s41598_025_98400_6 crossref_primary_10_1007_s11227_023_05486_8 crossref_primary_10_1155_2022_4639208 crossref_primary_10_1007_s13369_023_08217_6 crossref_primary_10_1007_s11227_023_05618_0 crossref_primary_10_1016_j_bspc_2025_108422 crossref_primary_10_1007_s13042_022_01617_4 crossref_primary_10_1038_s41598_024_61434_3 crossref_primary_10_1016_j_advengsoft_2024_103696 crossref_primary_10_1007_s13369_024_09702_2 crossref_primary_10_1007_s40435_025_01814_3 crossref_primary_10_1016_j_advengsoft_2024_103694 crossref_primary_10_1007_s42235_023_00447_6 crossref_primary_10_1080_15567036_2022_2086324 crossref_primary_10_1111_exsy_13224 crossref_primary_10_1007_s11227_022_04755_2 crossref_primary_10_3390_math11122728 crossref_primary_10_1007_s10462_023_10416_4 crossref_primary_10_1007_s10489_021_03037_3 crossref_primary_10_3390_act12100396 crossref_primary_10_1016_j_asoc_2023_110881 crossref_primary_10_1016_j_egyr_2022_05_231 crossref_primary_10_1108_K_07_2023_1210 crossref_primary_10_3390_en16155800 crossref_primary_10_1007_s13198_024_02609_z crossref_primary_10_1016_j_heliyon_2023_e16827 crossref_primary_10_3390_electronics13214215 crossref_primary_10_1093_ce_zkac010 crossref_primary_10_1016_j_eswa_2024_126197 crossref_primary_10_1016_j_jestch_2023_101408 crossref_primary_10_1016_j_knosys_2023_110454 crossref_primary_10_1016_j_knosys_2024_111960 crossref_primary_10_3390_s22030855 crossref_primary_10_1007_s00521_023_08230_8 crossref_primary_10_3233_JIFS_222413 crossref_primary_10_1016_j_heliyon_2024_e40068 crossref_primary_10_1007_s40815_022_01397_7 crossref_primary_10_1038_s41598_024_55040_6 crossref_primary_10_1515_mt_2022_0013 crossref_primary_10_1515_mt_2022_0012 crossref_primary_10_1515_mt_2022_0259 crossref_primary_10_1016_j_est_2025_116342 crossref_primary_10_1016_j_energy_2023_127069 crossref_primary_10_1080_10255842_2025_2501636 crossref_primary_10_1007_s00521_022_08179_0 crossref_primary_10_1016_j_optcom_2025_131577 crossref_primary_10_1007_s11227_023_05331_y crossref_primary_10_1016_j_energy_2024_131963 crossref_primary_10_3390_polym15010233 crossref_primary_10_1109_ACCESS_2021_3066329 crossref_primary_10_1007_s41870_024_01861_7 crossref_primary_10_1016_j_jksuci_2023_02_015 crossref_primary_10_1007_s10586_024_04293_x crossref_primary_10_1016_j_asoc_2022_109394 crossref_primary_10_1061_JCEMD4_COENG_16487 crossref_primary_10_1016_j_matcom_2023_04_020 crossref_primary_10_1007_s10706_025_03275_z crossref_primary_10_3390_biomimetics8040377 crossref_primary_10_1016_j_isatra_2025_07_023 crossref_primary_10_3390_app11178231 crossref_primary_10_1016_j_tafmec_2022_103627 crossref_primary_10_1080_10589759_2023_2274015 crossref_primary_10_1016_j_compeleceng_2025_110533 crossref_primary_10_1016_j_swevo_2023_101457 crossref_primary_10_1016_j_eswa_2023_120482 crossref_primary_10_3390_app11125620 crossref_primary_10_1016_j_engappai_2022_105202 crossref_primary_10_1038_s41598_024_60821_0 crossref_primary_10_1007_s10115_022_01746_w crossref_primary_10_3390_su14169882 crossref_primary_10_1007_s11063_023_11321_1 crossref_primary_10_52254_1857_0070_2025_2_66_05 crossref_primary_10_1016_j_engappai_2023_106959 crossref_primary_10_1109_ACCESS_2022_3142859 crossref_primary_10_1007_s11831_023_10030_1 crossref_primary_10_1016_j_physleta_2025_130430 crossref_primary_10_1007_s11227_022_04769_w crossref_primary_10_1016_j_bspc_2023_105806 crossref_primary_10_1007_s11831_024_10217_0 crossref_primary_10_1016_j_knosys_2022_110011 crossref_primary_10_1016_j_knosys_2025_114273 crossref_primary_10_1007_s13369_023_07803_y crossref_primary_10_1007_s10462_023_10537_w crossref_primary_10_1016_j_ifacsc_2025_100304 crossref_primary_10_3390_biomimetics8040381 crossref_primary_10_1016_j_jobe_2023_106274 crossref_primary_10_1007_s12530_024_09585_6 crossref_primary_10_1016_j_istruc_2022_08_064 crossref_primary_10_1016_j_energy_2024_131024 crossref_primary_10_3390_pr12071321 crossref_primary_10_1371_journal_pone_0275346 crossref_primary_10_1007_s11227_025_07452_y crossref_primary_10_3390_math10224197 crossref_primary_10_1007_s12652_025_05000_3 crossref_primary_10_1007_s11831_022_09800_0 crossref_primary_10_1016_j_eswa_2021_116001 crossref_primary_10_3390_biomimetics8080619 crossref_primary_10_1007_s10586_025_05280_6 crossref_primary_10_1155_2022_2721490 crossref_primary_10_1016_j_eswa_2025_127375 crossref_primary_10_1007_s12083_024_01786_9 crossref_primary_10_3390_app12105080 crossref_primary_10_3390_app14083289 crossref_primary_10_1007_s10489_021_03080_0 crossref_primary_10_1515_mt_2022_0119 crossref_primary_10_1109_ACCESS_2024_3392482 crossref_primary_10_1016_j_jer_2023_11_024 crossref_primary_10_3389_fenvs_2022_1055807 crossref_primary_10_1007_s11042_024_19211_x crossref_primary_10_3390_sym13122388 crossref_primary_10_1093_ijlct_ctae064 crossref_primary_10_1016_j_cose_2024_103751 crossref_primary_10_1016_j_eswa_2021_115131 crossref_primary_10_3390_su142214766 crossref_primary_10_7717_peerj_cs_910 crossref_primary_10_1016_j_heliyon_2024_e32712 crossref_primary_10_1007_s13042_022_01642_3 crossref_primary_10_1038_s41598_024_70731_w crossref_primary_10_32604_cmc_2022_025939 crossref_primary_10_1038_s41598_024_54991_0 crossref_primary_10_1007_s11771_023_5514_2 crossref_primary_10_1016_j_egyr_2021_08_198 crossref_primary_10_1016_j_heliyon_2024_e31629 crossref_primary_10_14201_adcaij_29969 crossref_primary_10_3390_s22051894 crossref_primary_10_3390_math10193466 crossref_primary_10_3390_math11040979 crossref_primary_10_3390_biomimetics9020065 crossref_primary_10_1016_j_ijepes_2021_107528 crossref_primary_10_3390_math11040851 crossref_primary_10_1016_j_asoc_2023_110573 crossref_primary_10_1002_dac_6052 crossref_primary_10_1038_s41598_024_78761_0 crossref_primary_10_3389_fenrg_2023_1326313 crossref_primary_10_1007_s11771_024_5680_x crossref_primary_10_1109_JIOT_2024_3398418 crossref_primary_10_3390_math11132953 crossref_primary_10_1007_s10489_021_02795_4 crossref_primary_10_1007_s13369_021_06307_x crossref_primary_10_1109_ACCESS_2022_3227510 crossref_primary_10_3103_S1060992X24700024 crossref_primary_10_1007_s00521_024_09524_1 crossref_primary_10_1007_s10462_023_10398_3 crossref_primary_10_1007_s11831_023_10034_x crossref_primary_10_1007_s41939_023_00333_y crossref_primary_10_1063_5_0108340 crossref_primary_10_1038_s41598_025_88745_3 crossref_primary_10_1109_ACCESS_2025_3566163 crossref_primary_10_1007_s42452_024_06044_4 crossref_primary_10_3390_math10010102 crossref_primary_10_1093_jcde_qwac040 crossref_primary_10_1002_oca_3100 crossref_primary_10_1371_journal_pone_0267633 crossref_primary_10_1007_s10586_024_04593_2 crossref_primary_10_1007_s11042_023_16651_9 crossref_primary_10_1016_j_matcom_2021_08_013 crossref_primary_10_3390_diagnostics13081422 crossref_primary_10_1007_s42488_025_00153_4 crossref_primary_10_3390_math11030707 crossref_primary_10_1007_s12046_022_01937_9 crossref_primary_10_1155_2022_7026728 crossref_primary_10_1038_s41598_023_32465_z crossref_primary_10_1002_ett_70226 crossref_primary_10_32604_cmes_2024_056693 crossref_primary_10_1007_s10586_024_04702_1 crossref_primary_10_3390_math9121316 crossref_primary_10_1016_j_compeleceng_2022_107862 crossref_primary_10_1016_j_heliyon_2024_e30757 crossref_primary_10_1016_j_egyr_2021_08_177 crossref_primary_10_1093_jcde_qwad017 crossref_primary_10_3390_biomimetics9010021 crossref_primary_10_1007_s10489_022_03397_4 crossref_primary_10_3389_fbioe_2022_1018895 crossref_primary_10_3390_diagnostics13050834 crossref_primary_10_1007_s13369_022_07408_x crossref_primary_10_1016_j_asoc_2021_107866 crossref_primary_10_1007_s43926_024_00070_9 crossref_primary_10_1007_s11356_023_29498_2 crossref_primary_10_1109_ACCESS_2025_3567556 crossref_primary_10_1007_s00500_025_10611_1 crossref_primary_10_1016_j_bspc_2024_107348 crossref_primary_10_1080_0305215X_2024_2386102 crossref_primary_10_1007_s42979_025_03873_x crossref_primary_10_1016_j_egyr_2024_12_020 crossref_primary_10_1007_s11831_022_09759_y crossref_primary_10_52254_1857_0070_2024_2_62_02 crossref_primary_10_1007_s00202_024_02530_5 crossref_primary_10_1016_j_asoc_2023_110597 crossref_primary_10_1016_j_apenergy_2024_123437 crossref_primary_10_1007_s00432_023_04699_x crossref_primary_10_1016_j_matcom_2021_10_032 crossref_primary_10_1007_s10489_021_02982_3 crossref_primary_10_1016_j_energy_2021_121532 crossref_primary_10_1007_s12597_024_00785_x crossref_primary_10_1155_2022_6627409 crossref_primary_10_61882_jsdp_22_2_43 crossref_primary_10_1016_j_jenvman_2023_119807 crossref_primary_10_3390_biomimetics9010008 crossref_primary_10_1007_s11276_024_03782_6 crossref_primary_10_3390_en16135144 crossref_primary_10_1007_s10489_021_02776_7 crossref_primary_10_1016_j_bspc_2025_107737 crossref_primary_10_1016_j_eswa_2021_115178 crossref_primary_10_1109_TGRS_2024_3462752 crossref_primary_10_1016_j_asoc_2023_110252 crossref_primary_10_1371_journal_pone_0290719 crossref_primary_10_1038_s41598_025_91911_2 crossref_primary_10_1109_ACCESS_2021_3108533 crossref_primary_10_1016_j_cie_2023_109080 crossref_primary_10_1016_j_matcom_2022_04_031 crossref_primary_10_1007_s12065_022_00762_7 crossref_primary_10_1007_s42835_023_01739_x crossref_primary_10_3390_biomimetics9010001 crossref_primary_10_3390_healthcare11040590 crossref_primary_10_1007_s12065_023_00892_6 crossref_primary_10_1080_10255842_2024_2431886 crossref_primary_10_3390_biomimetics10060411 crossref_primary_10_1007_s10462_024_10747_w crossref_primary_10_1002_dac_6100 crossref_primary_10_1016_j_jobe_2024_109748 crossref_primary_10_3390_en16052086 crossref_primary_10_1016_j_eswa_2024_124882 crossref_primary_10_3390_biomimetics7040204 crossref_primary_10_2478_jaiscr_2025_0009 crossref_primary_10_3390_electronics12091961 crossref_primary_10_3390_biomimetics9030186 crossref_primary_10_1109_ACCESS_2021_3117567 crossref_primary_10_1016_j_matcom_2022_11_020 crossref_primary_10_3390_su142214928 crossref_primary_10_1016_j_eswa_2024_124529 crossref_primary_10_3390_computation11110230 crossref_primary_10_1007_s00521_021_06807_9 crossref_primary_10_1007_s10489_022_03428_0 crossref_primary_10_1007_s42044_025_00252_w crossref_primary_10_1007_s11227_023_05773_4 crossref_primary_10_32604_cmes_2024_055171 crossref_primary_10_52254_1857_0070_2023_3_59_01 crossref_primary_10_1038_s41598_022_24343_x crossref_primary_10_1007_s10489_022_03977_4 crossref_primary_10_1007_s10489_021_03133_4 crossref_primary_10_3390_math13172799 crossref_primary_10_1016_j_chaos_2024_114723 crossref_primary_10_1016_j_compbiomed_2023_106691 crossref_primary_10_1016_j_knosys_2023_111257 crossref_primary_10_1155_2021_7788491 crossref_primary_10_1016_j_conengprac_2024_106061 crossref_primary_10_1109_TCBB_2023_3305429 crossref_primary_10_1007_s11071_024_09829_9 crossref_primary_10_1007_s10462_023_10581_6 crossref_primary_10_1016_j_jece_2024_114043 crossref_primary_10_3390_app12189170 crossref_primary_10_1007_s10586_024_05055_5 crossref_primary_10_1016_j_cie_2022_107974 crossref_primary_10_1080_1448837X_2024_2355004 crossref_primary_10_1002_ett_70026 crossref_primary_10_1080_0952813X_2024_2338495 crossref_primary_10_1109_TMECH_2022_3206435 crossref_primary_10_1016_j_jmapro_2024_10_001 crossref_primary_10_3390_rs13040755 crossref_primary_10_1186_s40537_024_00917_6 crossref_primary_10_1007_s11042_023_18085_9 crossref_primary_10_1038_s41598_021_01018_7 crossref_primary_10_1007_s10586_024_04602_4 crossref_primary_10_3390_axioms12100907 crossref_primary_10_1038_s41598_023_36066_8 crossref_primary_10_1016_j_chaos_2023_114028 crossref_primary_10_1007_s00366_021_01487_4 crossref_primary_10_3390_eng6080174 crossref_primary_10_1016_j_bspc_2024_106732 crossref_primary_10_1080_0954898X_2025_2503791 crossref_primary_10_1155_2022_3343505 crossref_primary_10_1109_ACCESS_2022_3216321 crossref_primary_10_1080_1448837X_2025_2529098 crossref_primary_10_1007_s11227_023_05579_4 crossref_primary_10_1016_j_sysarc_2023_102871 crossref_primary_10_1016_j_aei_2024_102354 crossref_primary_10_1016_j_energy_2023_127557 crossref_primary_10_1016_j_est_2021_103848 crossref_primary_10_1007_s10489_022_03438_y crossref_primary_10_1109_JIOT_2024_3448256 crossref_primary_10_1007_s10489_021_02849_7 crossref_primary_10_1016_j_advengsoft_2022_103404 crossref_primary_10_1016_j_compbiomed_2022_106075 crossref_primary_10_1002_ett_4733 crossref_primary_10_1109_ACCESS_2021_3096726 crossref_primary_10_1007_s12597_025_00973_3 crossref_primary_10_1016_j_ijhydene_2023_02_071 crossref_primary_10_3233_JIFS_221098 crossref_primary_10_1080_13813455_2025_2524182 crossref_primary_10_3390_a17110478 crossref_primary_10_1007_s00521_021_06273_3 crossref_primary_10_32604_cmc_2024_050863 crossref_primary_10_1016_j_bspc_2024_106987 crossref_primary_10_1007_s00500_022_07033_8 crossref_primary_10_1007_s12065_024_00995_8 crossref_primary_10_1038_s41598_024_53602_2 crossref_primary_10_1080_0954898X_2024_2373127 crossref_primary_10_1080_0305215X_2025_2501647 crossref_primary_10_32604_cmc_2025_058894 crossref_primary_10_1007_s10462_022_10233_1 crossref_primary_10_1007_s10462_024_11104_7 crossref_primary_10_1007_s10489_022_03962_x crossref_primary_10_1016_j_rsase_2024_101424 crossref_primary_10_3390_math13172888 crossref_primary_10_1093_jcde_qwae089 crossref_primary_10_32604_cmes_2024_053236 crossref_primary_10_3390_en15228499 crossref_primary_10_1007_s00521_023_08657_z crossref_primary_10_3390_math12071059 crossref_primary_10_1371_journal_pone_0285211 crossref_primary_10_3390_biomimetics8060508 crossref_primary_10_3390_biomimetics8060507 crossref_primary_10_26599_Jic_2025_9180087 crossref_primary_10_1016_j_engappai_2022_104722 crossref_primary_10_1007_s10064_025_04338_4 crossref_primary_10_1016_j_asoc_2025_113527 crossref_primary_10_1109_ACCESS_2022_3177218 crossref_primary_10_1007_s13042_025_02620_1 crossref_primary_10_1016_j_cma_2023_116307 crossref_primary_10_1007_s10489_021_03155_y crossref_primary_10_1016_j_tust_2023_105508 crossref_primary_10_1007_s00521_025_11637_0 crossref_primary_10_3390_biomimetics10080517 crossref_primary_10_1007_s11356_022_19426_1 crossref_primary_10_1016_j_cma_2023_116200 crossref_primary_10_1007_s00521_022_07574_x crossref_primary_10_1007_s44196_025_00823_6 crossref_primary_10_1016_j_energy_2025_136944 crossref_primary_10_1007_s10586_025_05201_7 crossref_primary_10_1016_j_cma_2023_116446 crossref_primary_10_1007_s12008_024_02136_y crossref_primary_10_1109_ACCESS_2021_3061529 crossref_primary_10_1007_s10489_022_03994_3 crossref_primary_10_1109_ACCESS_2022_3153493 crossref_primary_10_1007_s00500_022_06886_3 crossref_primary_10_1080_15567036_2024_2387239 crossref_primary_10_1109_ACCESS_2023_3272356 crossref_primary_10_1007_s10462_024_10857_5 crossref_primary_10_1016_j_cmpb_2021_106244 crossref_primary_10_1007_s12145_023_00963_3 crossref_primary_10_3390_s23218783 crossref_primary_10_1007_s00521_022_07925_8 crossref_primary_10_1007_s12652_022_04347_1 crossref_primary_10_1016_j_compbiomed_2023_107237 crossref_primary_10_3390_electronics10172057 crossref_primary_10_1016_j_neucom_2025_129687 crossref_primary_10_1016_j_renene_2025_122866 crossref_primary_10_1016_j_soildyn_2025_109530 crossref_primary_10_1109_ACCESS_2024_3359587 crossref_primary_10_1631_FITEE_2200237 crossref_primary_10_1016_j_euromechflu_2025_204305 crossref_primary_10_1007_s10462_022_10234_0 crossref_primary_10_1016_j_aej_2025_02_037 crossref_primary_10_1142_S0218126625502469 crossref_primary_10_1016_j_rineng_2025_105130 crossref_primary_10_1177_18724981241292884 crossref_primary_10_1016_j_asoc_2022_108717 crossref_primary_10_1016_j_cviu_2024_103933 crossref_primary_10_1016_j_neucom_2023_03_065 crossref_primary_10_1109_JSEN_2023_3256009 crossref_primary_10_1016_j_eswa_2025_129195 crossref_primary_10_3390_biomimetics10010031 crossref_primary_10_1016_j_energy_2022_124363 crossref_primary_10_1016_j_ijhydene_2022_09_129 crossref_primary_10_1016_j_applthermaleng_2024_125005 crossref_primary_10_1002_cpe_7705 crossref_primary_10_1007_s11235_022_00883_5 crossref_primary_10_3390_pr10112254 crossref_primary_10_3390_biomimetics10080537 crossref_primary_10_1016_j_cie_2023_109237 crossref_primary_10_3390_math12030435 crossref_primary_10_1016_j_aej_2025_02_061 crossref_primary_10_1155_er_3457520 crossref_primary_10_1016_j_knosys_2022_109615 crossref_primary_10_1016_j_chemolab_2025_105478 crossref_primary_10_1007_s40747_023_01082_8 crossref_primary_10_1155_2023_9709608 crossref_primary_10_1007_s11227_024_06616_6 crossref_primary_10_1016_j_jpdc_2024_104850 crossref_primary_10_1109_ACCESS_2023_3287859 crossref_primary_10_1016_j_eswa_2022_117127 crossref_primary_10_1007_s12145_022_00825_4 crossref_primary_10_3390_biomimetics9070419 crossref_primary_10_3390_computers11120170 crossref_primary_10_1093_jcde_qwaf014 crossref_primary_10_1016_j_eswa_2024_123362 crossref_primary_10_1109_ACCESS_2022_3229964 crossref_primary_10_1007_s42835_021_00862_x crossref_primary_10_1093_jcde_qwac094 crossref_primary_10_1002_jnm_70030 crossref_primary_10_1016_j_heliyon_2024_e38783 crossref_primary_10_1002_cpe_6991 crossref_primary_10_1080_02286203_2023_2298174 crossref_primary_10_3390_s22124492 crossref_primary_10_1007_s42044_023_00160_x crossref_primary_10_1007_s42235_022_00223_y crossref_primary_10_3390_math10162960 crossref_primary_10_1007_s00521_024_10009_4 crossref_primary_10_1007_s12530_023_09485_1 crossref_primary_10_1109_ACCESS_2022_3157400 crossref_primary_10_1007_s11227_023_05513_8 crossref_primary_10_1007_s11042_023_15693_3 crossref_primary_10_1016_j_engappai_2022_104920 crossref_primary_10_1007_s11042_023_17148_1 crossref_primary_10_1007_s11831_024_10168_6 crossref_primary_10_1615_TelecomRadEng_2025053207 crossref_primary_10_1007_s10489_023_04473_z crossref_primary_10_1007_s00500_023_09023_w crossref_primary_10_1007_s10489_022_04059_1 crossref_primary_10_1016_j_compbiomed_2023_107389 crossref_primary_10_1038_s41598_023_49754_2 crossref_primary_10_1155_2022_6227794 crossref_primary_10_1016_j_knosys_2024_112347 crossref_primary_10_1007_s11042_023_15781_4 crossref_primary_10_1007_s00477_022_02178_2 crossref_primary_10_1038_s41598_022_18001_5 crossref_primary_10_1016_j_infrared_2025_105788 crossref_primary_10_1007_s11831_022_09876_8 crossref_primary_10_1007_s11554_024_01584_9 crossref_primary_10_3390_axioms11030095 crossref_primary_10_1007_s11831_025_10363_z crossref_primary_10_1038_s41598_024_59960_1 crossref_primary_10_1016_j_autcon_2024_105653 crossref_primary_10_1016_j_matcom_2022_06_007 crossref_primary_10_3390_en15041587 crossref_primary_10_1007_s00521_021_06634_y crossref_primary_10_1007_s10973_024_13628_0 crossref_primary_10_1080_01431161_2024_2326041 crossref_primary_10_1016_j_knosys_2023_111081 crossref_primary_10_1002_nbm_70036 crossref_primary_10_1007_s11630_025_2125_2 crossref_primary_10_1007_s13349_022_00638_5 crossref_primary_10_1007_s00500_023_08468_3
Cites_doi	10.1007/11579427_66 10.1109/CEC.1999.782657 10.1115/1.2919393 10.1016/j.eswa.2020.113364 10.1016/j.engappai.2020.103731 10.1016/j.asoc.2013.05.010 10.1038/scientificamerican0792-66 10.1016/j.knosys.2015.07.006 10.1016/j.compstruc.2012.09.003 10.1016/j.advengsoft.2017.03.014 10.1007/s00521-018-3592-0 10.1007/s10462-017-9605-z 10.1007/BF02986750 10.1016/j.eswa.2016.04.018 10.1016/S0166-3615(99)00046-9 10.1007/s00521-019-04611-0 10.1016/j.ins.2015.09.051 10.1016/j.knosys.2015.12.022 10.1016/j.ins.2009.03.004 10.1109/4235.585893 10.1016/j.advengsoft.2013.12.007 10.1007/s10462-012-9328-0 10.1016/j.compchemeng.2019.106656 10.1016/j.ins.2015.10.001 10.1109/ICENCO.2017.8289778 10.1016/j.advengsoft.2017.07.002 10.1016/j.compstruc.2012.07.010 10.1007/s40747-018-0071-2 10.1007/s00707-012-0745-6 10.1145/2480741.2480752 10.1016/j.advengsoft.2016.01.008 10.1016/j.asoc.2015.07.028 10.1016/j.swevo.2016.12.005 10.1016/j.knosys.2018.08.030 10.1515/jaiscr-2015-0001 10.1504/IJICA.2011.037947 10.1126/science.220.4598.671 10.1016/j.future.2019.07.015 10.1016/j.knosys.2014.07.025 10.1016/j.knosys.2019.105190 10.1016/j.asoc.2012.11.026 10.1007/s00707-009-0270-4 10.1109/TEVC.2009.2033580 10.1016/j.asoc.2020.106347 10.1016/j.future.2019.02.028 10.1016/j.swevo.2015.07.002 10.1016/j.asoc.2015.03.035
ContentType	Journal Article
Copyright	Springer Science+Business Media, LLC, part of Springer Nature 2020 Springer Science+Business Media, LLC, part of Springer Nature 2020.
Copyright_xml	– notice: Springer Science+Business Media, LLC, part of Springer Nature 2020 – notice: Springer Science+Business Media, LLC, part of Springer Nature 2020.
DBID	AAYXX CITATION 3V. 7SC 7WY 7WZ 7XB 87Z 8AL 8FD 8FE 8FG 8FK 8FL ABJCF ABUWG AFKRA ARAPS AZQEC BENPR BEZIV BGLVJ CCPQU DWQXO FRNLG F~G GNUQQ HCIFZ JQ2 K60 K6~ K7- L.- L6V L7M L~C L~D M0C M0N M7S P5Z P62 PHGZM PHGZT PKEHL PQBIZ PQBZA PQEST PQGLB PQQKQ PQUKI PRINS PSYQQ PTHSS Q9U
DOI	10.1007/s10489-020-01893-z
DatabaseName	CrossRef ProQuest Central (Corporate) Computer and Information Systems Abstracts ABI/INFORM Collection ABI/INFORM Global (PDF only) ProQuest Central (purchase pre-March 2016) ABI/INFORM Collection Computing Database (Alumni Edition) Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central (Alumni) (purchase pre-March 2016) ABI/INFORM Collection (Alumni) ProQuest Materials Science & Engineering ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials ProQuest Central Business Premium Collection Technology Collection ProQuest One ProQuest Central Business Premium Collection (Alumni) ABI/INFORM Global (Corporate) ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection ProQuest Business Collection (Alumni Edition) ProQuest Business Collection Computer Science Database ABI/INFORM Professional Advanced ProQuest Engineering Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ABI/INFORM Global Computing Database Engineering Database ProQuest advanced technologies & aerospace journals ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Business (UW System Shared) ProQuest One Business (Alumni) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China ProQuest One Psychology Engineering Collection ProQuest Central Basic
DatabaseTitle	CrossRef ProQuest Business Collection (Alumni Edition) ProQuest One Psychology Computer Science Database ProQuest Central Student ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection Computer and Information Systems Abstracts SciTech Premium Collection ProQuest Central China ABI/INFORM Complete ProQuest One Applied & Life Sciences ProQuest Central (New) Engineering Collection Advanced Technologies & Aerospace Collection Business Premium Collection ABI/INFORM Global Engineering Database ProQuest One Academic Eastern Edition ProQuest Technology Collection ProQuest Business Collection ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ABI/INFORM Global (Corporate) ProQuest One Business Technology Collection Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest Central ABI/INFORM Professional Advanced ProQuest Engineering Collection ProQuest Central Korea Advanced Technologies Database with Aerospace ABI/INFORM Complete (Alumni Edition) ProQuest Computing ABI/INFORM Global (Alumni Edition) ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest SciTech Collection Computer and Information Systems Abstracts Professional Advanced Technologies & Aerospace Database Materials Science & Engineering Collection ProQuest One Business (Alumni) ProQuest Central (Alumni) Business Premium Collection (Alumni)
DatabaseTitleList	ProQuest Business Collection (Alumni Edition)
Database_xml	– sequence: 1 dbid: BENPR name: ProQuest Central Database Suite (ProQuest) url: https://www.proquest.com/central sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Computer Science
EISSN	1573-7497
EndPage	1551
ExternalDocumentID	10_1007_s10489_020_01893_z
GrantInformation_xml	– fundername: University of Electronic Science and Technology of China (UESTC) and National Natural Science Foundation of China (NSFC) grantid: Grant No. 61772120.
GroupedDBID	-4Z -59 -5G -BR -EM -Y2 -~C -~X .86 .DC .VR 06D 0R~ 0VY 1N0 1SB 2.D 203 23M 28- 2J2 2JN 2JY 2KG 2LR 2P1 2VQ 2~H 30V 3V. 4.4 406 408 409 40D 40E 5GY 5QI 5VS 67Z 6NX 77K 7WY 8FE 8FG 8FL 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AAOBN AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDZT ABECU ABFTV ABHLI ABHQN ABIVO ABJCF ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABQSL ABSXP ABTAH ABTEG ABTHY ABTKH ABTMW ABULA ABUWG ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACHXU ACIWK ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACSNA ACZOJ ADHHG ADHIR ADIMF ADINQ ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFGCZ AFKRA AFLOW AFQWF AFWTZ AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARAPS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN AZQEC B-. BA0 BBWZM BDATZ BENPR BEZIV BGLVJ BGNMA BPHCQ BSONS CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DWQXO EBLON EBS EIOEI EJD ESBYG FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRNLG FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNUQQ GNWQR GQ6 GQ7 GQ8 GROUPED_ABI_INFORM_COMPLETE GXS H13 HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ I09 IHE IJ- IKXTQ ITM IWAJR IXC IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ K60 K6V K6~ K7- KDC KOV KOW L6V LAK LLZTM M0C M0N M4Y M7S MA- N2Q N9A NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM OVD P19 P2P P62 P9O PF0 PQBIZ PQBZA PQQKQ PROAC PSYQQ PT4 PT5 PTHSS Q2X QOK QOS R4E R89 R9I RHV RNI RNS ROL RPX RSV RZC RZE RZK S16 S1Z S26 S27 S28 S3B SAP SCJ SCLPG SCO SDH SDM SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 T16 TEORI TSG TSK TSV TUC U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR Z45 Z7R Z7X Z7Z Z81 Z83 Z88 Z8M Z8N Z8R Z8T Z8U Z8W Z92 ZMTXR ZY4 ~A9 ~EX 77I AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC ADHKG ADKFA AEZWR AFDZB AFFHD AFHIU AFOHR AGQPQ AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION PHGZM PHGZT PQGLB 7SC 7XB 8AL 8FD 8FK JQ2 L.- L7M L~C L~D PKEHL PQEST PQUKI PRINS Q9U
ID	FETCH-LOGICAL-c385t-88124d6792cbea30cceb052aab7858b0de3b9f0647ad5198d877f0ff78bc98963
IEDL.DBID	K7-
ISICitedReferencesCount	823
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000573749800001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0924-669X
IngestDate	Wed Nov 05 14:47:06 EST 2025 Tue Nov 18 22:37:03 EST 2025 Sat Nov 29 05:33:21 EST 2025 Fri Feb 21 02:48:39 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	3
Keywords	Exploration and exploitation Buoyant force Metaheuristic Archimedes’ principle Optimization
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c385t-88124d6792cbea30cceb052aab7858b0de3b9f0647ad5198d877f0ff78bc98963
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-8127-7233
PQID	2487630319
PQPubID	326365
PageCount	21
ParticipantIDs	proquest_journals_2487630319 crossref_citationtrail_10_1007_s10489_020_01893_z crossref_primary_10_1007_s10489_020_01893_z springer_journals_10_1007_s10489_020_01893_z
PublicationCentury	2000
PublicationDate	2021-03-01
PublicationDateYYYYMMDD	2021-03-01
PublicationDate_xml	– month: 03 year: 2021 text: 2021-03-01 day: 01
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York – name: Boston
PublicationSubtitle	The International Journal of Research on Intelligent Systems for Real Life Complex Problems
PublicationTitle	Applied intelligence (Dordrecht, Netherlands)
PublicationTitleAbbrev	Appl Intell
PublicationYear	2021
Publisher	Springer US Springer Nature B.V
Publisher_xml	– name: Springer US – name: Springer Nature B.V
References	HussainKSallehMNMChengSShiYMetaheuristic research: a comprehensive surveyArtif Intell Rev201952421912233 AbedinpourshotorbanHShamsuddinSMBeheshtiZJawawiDNAElectromagnetic field optimization: a physics-inspired metaheuristic optimization algorithmSwarm Evol Comput201626822 RorresCAcross neighborhood search for numerical optimizationInf Sci2016329597618 HousseinEHHosneyMEOlivaDMohamedWMHassaballahMA novel hybrid Harris hawks optimization and support vector machines for drug design and discoveryComput Chem Eng2020133106656 RashediENezamabadi-pourHSaryazdiSGsa: a gravitational search algorithmInf Sci200917913223222481177.90378 Neggaz N, Houssein EH, Hussain K (2020) An efficient henry gas solubility optimization for feature selection. Exp Syst Appl 113364 Eberhart RC, Kennedy J (1995) A new optimizer using particle swarm theory. In: MHS’95 Proceedings of the sixth international symposium on micro machine and human science, pp 39–43 HeidariAAMirjaliliSFarisHAljarahIMafarjaMChenHHarris hawks optimization: algorithm and applicationsFuture Gener Comput Syst201997849872 MavrovouniotisMLiCYangSA survey of swarm intelligence for dynamic optimization: algorithms and applicationsSwarm Evol Comput201733117 ChengSShiYQinQZhangQBaiRPopulation diversity maintenance in brain storm optimization algorithmJ Artif Intell Soft Comput Res2014428397 LamAYSLiVOKChemical-reaction-inspired metaheuristic for optimizationIEEE Trans Evol Comput2010143381399 Mezura-Montes E, Coello CAC (2005) Useful infeasible solutions in engineering optimization with evolutionary algorithms. In: Mexican international conference on artificial intelligence, pp 652–662 KavehATalatahariSA novel heuristic optimization method: charged system searchActa Mech20102132672891397.65094 ČrepinšekMLiuS-HMernikMExploration and exploitation in evolutionary algorithms: a surveyACM Comput Surv20134531351293.68251 ZhaoWWangLAn effective bacterial foraging optimizer for global optimizationInf Sci2016329719735 HollandJHGenetic algorithmsSci Am199226716672 JavidyBHatamlouAMirjaliliSIons motion algorithm for solving optimization problemsAppl Soft Comput2015327279 HussainKSallehMNMChengSShiYOn the exploration and exploitation in popular swarm-based metaheuristic algorithmsNeural Comput Appl2018311176657683 EskandarHSadollahABahreininejadAHamdiMWater cycle algorithm—a novel metaheuristic optimization method for solving constrained engineering optimization problemsComput Struct20121101151166 KirkpatrickSGelattCDVecchiMPOptimization by simulated annealingScience198322045986716807024851225.90162 HussainSAhmadAIMutlagAHLightning search algorithmAppl Soft Comput201536315333 TaradehMMafarjaMHeidariAAFarisHAljarahIMirjaliliSFujitaHAn evolutionary gravitational search-based feature selectionAppl Soft Comput2019497219239 MirjaliliSMirjaliliSMLewisAGrey wolf optimizerAdv Eng Softw2014694661 KarAKBio inspired computing—a review of algorithms and scope of applicationsExp Syst Appl2016592032 KavehADadrasAA novel meta-heuristic optimization algorithm: thermal exchange optimizationAdv Eng Softw20171106984 KarabogaDGorkemliBOzturkCKarabogaNA comprehensive survey: artificial bee colony (abc) algorithm and applicationsArtif Intell Rev20144212157 HashimFAHousseinEHHussainKMabroukMSAl-AtabanyWA modified Henry gas solubility optimization for solving motif discovery problemNeural Comput Appl202032141075910771 SalimiHStochastic fractal searchKnowl-Based Syst201575118 FaramarziAHeidarinejadMStephensBMirjaliliSEquilibrium optimizer: a novel optimization algorithmKnowl-Based Syst2020191105190 KavehAKhayatazadMA new meta-heuristic method: ray optimizationComput Struct2012112283294 MirjaliliSGandomiAHMirjaliliSZSaremiSFarisHMirjaliliSMSalp swarm algorithmAdv Eng Softw2017114163191 ZhaoWWangLZhangZAtom search optimization and its application to solve a hydrogeologic parameter estimation problemKnowl-Based Syst201989283304 HousseinEHSaadMRHashimFAShabanHHassaballahMLévy flight distribution: a new metaheuristic algorithm for solving engineering optimization problemsEng Appl Artif Intell202094103731 ChengSLuHLeiXShiYA quarter century of particle swarm optimizationComplex Intell Syst201843227239 CoelloCACUse of a self-adaptive penalty approach for engineering optimization problemsComput Ind2000412113127 RorresCCompleting book ii of archimedes’s on floating bodiesMath Intell2004263324220880131069.01004 LiuS-HMernikMHrnčičDČrepinšekMA parameter control method of evolutionary algorithms using exploration and exploitation measures with a practical application for fitting sovova’s mass transfer modelAppl Soft Comput201313937923805 MirjaliliSMLewisAThe whale optimization algorithmAdv Eng Softw2016955167 KavehAShareMAMMoslehiMMagnetic charged system search: a new meta-heuristic algorithm for optimizationActa Mech20132241851071318.78011 SadollahABahreininejadAEskandarHHamdiMMine blast algorithm: a new population based algorithm for solving constrained engineering optimization problemsAppl Soft Comput201313525922612 KannanBKramerSNAn augmented lagrange multiplier based method for mixed integer discrete continuous optimization and its applications to mechanical designJ Mech Des19941162405411 ČrepinšekMMernikMLiuS-HAnalysis of exploration and exploitation in evolutionary algorithms by ancestry treesInt J Innov Comput Appl20113111191293.68251 Wu G, Mallipeddi R, Suganthan P (2017) Problem definitions and evaluation criteria for the cec 2017 competition on constrained real-parameter optimization, National University of Defense Technology, Changsha, Hunan, PR China and Kyungpook National University, Daegu, South Korea and Nanyang Technological University, Singapore, Technical Report. http://www.ntu.edu.sg/home/EPNSugan/index_files/CEC2017 HashimFAHousseinEHMabroukMSAl-AtabanyWMirjaliliSHenry gas solubility optimization: a novel physics-based algorithmFuture Gener Comput Syst2019101646667 MirjaliliSMoth-flame optimization algorithmKnowl-Based Syst201589228249 WolpertDHMacreadyWGNo free lunch theorems for optimizationIEEE Trans Evol Comput1997116782 MirjaliliSSca: a sine cosine algorithm for solving optimization problemsKnowl-Based Syst20169696120133 Hashim F, Mabrouk MS, Al-Atabany W (2017) GWOMF: Grey Wolf Optimization for motif finding. In: 2017 13th international computer engineering conference (ICENCO), pp 141–146 Dorigo M, Di Caro G (1999) Ant colony optimization: a new meta-heuristic. In: Proceedings of the 1999 congress on evolutionary computation, 1999 CEC 99, pp 1470–1477 Elaziz MA, Heidari AA, Fujita H, Moayedi H (2020) A competitive chain-based Harris Hawks Optimizer for global optimization and multi-level image thresholding problems. Appl Soft Comput 106347, in press M Taradeh (1893_CR2) 2019; 497 H Salimi (1893_CR28) 2015; 75 A Kaveh (1893_CR33) 2013; 224 A Faramarzi (1893_CR32) 2020; 191 B Kannan (1893_CR50) 1994; 116 W Zhao (1893_CR31) 2019; 89 AA Heidari (1893_CR4) 2019; 97 EH Houssein (1893_CR5) 2020; 133 S Cheng (1893_CR40) 2014; 4 S Cheng (1893_CR44) 2018; 4 C Rorres (1893_CR39) 2016; 329 DH Wolpert (1893_CR37) 1997; 1 1893_CR14 1893_CR12 EH Houssein (1893_CR3) 2020; 94 S Kirkpatrick (1893_CR11) 1983; 220 JH Holland (1893_CR13) 1992; 267 CAC Coello (1893_CR47) 2000; 41 H Abedinpourshotorban (1893_CR34) 2016; 26 M Črepinšek (1893_CR43) 2011; 3 M Črepinšek (1893_CR42) 2013; 45 AYS Lam (1893_CR26) 2010; 14 K Hussain (1893_CR10) 2019; 52 1893_CR49 S-H Liu (1893_CR21) 2013; 13 1893_CR46 1893_CR1 B Javidy (1893_CR35) 2015; 32 S Mirjalili (1893_CR27) 2016; 96 FA Hashim (1893_CR7) 2020; 32 AK Kar (1893_CR9) 2016; 59 1893_CR6 1893_CR8 A Kaveh (1893_CR24) 2012; 112 W Zhao (1893_CR17) 2016; 329 S Mirjalili (1893_CR18) 2015; 89 H Eskandar (1893_CR45) 2012; 110 E Rashedi (1893_CR23) 2009; 179 S Mirjalili (1893_CR19) 2017; 114 S Hussain (1893_CR30) 2015; 36 A Kaveh (1893_CR22) 2010; 213 FA Hashim (1893_CR25) 2019; 101 M Mavrovouniotis (1893_CR36) 2017; 33 C Rorres (1893_CR38) 2004; 26 D Karaboga (1893_CR15) 2014; 42 SM Mirjalili (1893_CR20) 2016; 95 S Mirjalili (1893_CR16) 2014; 69 A Sadollah (1893_CR48) 2013; 13 A Kaveh (1893_CR29) 2017; 110 K Hussain (1893_CR41) 2018; 31
References_xml	– reference: HussainSAhmadAIMutlagAHLightning search algorithmAppl Soft Comput201536315333 – reference: SadollahABahreininejadAEskandarHHamdiMMine blast algorithm: a new population based algorithm for solving constrained engineering optimization problemsAppl Soft Comput201313525922612 – reference: ZhaoWWangLZhangZAtom search optimization and its application to solve a hydrogeologic parameter estimation problemKnowl-Based Syst201989283304 – reference: Eberhart RC, Kennedy J (1995) A new optimizer using particle swarm theory. In: MHS’95 Proceedings of the sixth international symposium on micro machine and human science, pp 39–43 – reference: KarabogaDGorkemliBOzturkCKarabogaNA comprehensive survey: artificial bee colony (abc) algorithm and applicationsArtif Intell Rev20144212157 – reference: TaradehMMafarjaMHeidariAAFarisHAljarahIMirjaliliSFujitaHAn evolutionary gravitational search-based feature selectionAppl Soft Comput2019497219239 – reference: HashimFAHousseinEHMabroukMSAl-AtabanyWMirjaliliSHenry gas solubility optimization: a novel physics-based algorithmFuture Gener Comput Syst2019101646667 – reference: KavehADadrasAA novel meta-heuristic optimization algorithm: thermal exchange optimizationAdv Eng Softw20171106984 – reference: LamAYSLiVOKChemical-reaction-inspired metaheuristic for optimizationIEEE Trans Evol Comput2010143381399 – reference: MavrovouniotisMLiCYangSA survey of swarm intelligence for dynamic optimization: algorithms and applicationsSwarm Evol Comput201733117 – reference: KarAKBio inspired computing—a review of algorithms and scope of applicationsExp Syst Appl2016592032 – reference: AbedinpourshotorbanHShamsuddinSMBeheshtiZJawawiDNAElectromagnetic field optimization: a physics-inspired metaheuristic optimization algorithmSwarm Evol Comput201626822 – reference: ČrepinšekMMernikMLiuS-HAnalysis of exploration and exploitation in evolutionary algorithms by ancestry treesInt J Innov Comput Appl20113111191293.68251 – reference: MirjaliliSMoth-flame optimization algorithmKnowl-Based Syst201589228249 – reference: SalimiHStochastic fractal searchKnowl-Based Syst201575118 – reference: KirkpatrickSGelattCDVecchiMPOptimization by simulated annealingScience198322045986716807024851225.90162 – reference: HussainKSallehMNMChengSShiYMetaheuristic research: a comprehensive surveyArtif Intell Rev201952421912233 – reference: HousseinEHSaadMRHashimFAShabanHHassaballahMLévy flight distribution: a new metaheuristic algorithm for solving engineering optimization problemsEng Appl Artif Intell202094103731 – reference: WolpertDHMacreadyWGNo free lunch theorems for optimizationIEEE Trans Evol Comput1997116782 – reference: KavehAKhayatazadMA new meta-heuristic method: ray optimizationComput Struct2012112283294 – reference: MirjaliliSSca: a sine cosine algorithm for solving optimization problemsKnowl-Based Syst20169696120133 – reference: ChengSLuHLeiXShiYA quarter century of particle swarm optimizationComplex Intell Syst201843227239 – reference: HashimFAHousseinEHHussainKMabroukMSAl-AtabanyWA modified Henry gas solubility optimization for solving motif discovery problemNeural Comput Appl202032141075910771 – reference: Hashim F, Mabrouk MS, Al-Atabany W (2017) GWOMF: Grey Wolf Optimization for motif finding. In: 2017 13th international computer engineering conference (ICENCO), pp 141–146 – reference: EskandarHSadollahABahreininejadAHamdiMWater cycle algorithm—a novel metaheuristic optimization method for solving constrained engineering optimization problemsComput Struct20121101151166 – reference: KannanBKramerSNAn augmented lagrange multiplier based method for mixed integer discrete continuous optimization and its applications to mechanical designJ Mech Des19941162405411 – reference: RashediENezamabadi-pourHSaryazdiSGsa: a gravitational search algorithmInf Sci200917913223222481177.90378 – reference: MirjaliliSGandomiAHMirjaliliSZSaremiSFarisHMirjaliliSMSalp swarm algorithmAdv Eng Softw2017114163191 – reference: FaramarziAHeidarinejadMStephensBMirjaliliSEquilibrium optimizer: a novel optimization algorithmKnowl-Based Syst2020191105190 – reference: CoelloCACUse of a self-adaptive penalty approach for engineering optimization problemsComput Ind2000412113127 – reference: Elaziz MA, Heidari AA, Fujita H, Moayedi H (2020) A competitive chain-based Harris Hawks Optimizer for global optimization and multi-level image thresholding problems. Appl Soft Comput 106347, in press – reference: MirjaliliSMirjaliliSMLewisAGrey wolf optimizerAdv Eng Softw2014694661 – reference: Wu G, Mallipeddi R, Suganthan P (2017) Problem definitions and evaluation criteria for the cec 2017 competition on constrained real-parameter optimization, National University of Defense Technology, Changsha, Hunan, PR China and Kyungpook National University, Daegu, South Korea and Nanyang Technological University, Singapore, Technical Report. http://www.ntu.edu.sg/home/EPNSugan/index_files/CEC2017 – reference: KavehATalatahariSA novel heuristic optimization method: charged system searchActa Mech20102132672891397.65094 – reference: Mezura-Montes E, Coello CAC (2005) Useful infeasible solutions in engineering optimization with evolutionary algorithms. In: Mexican international conference on artificial intelligence, pp 652–662 – reference: HeidariAAMirjaliliSFarisHAljarahIMafarjaMChenHHarris hawks optimization: algorithm and applicationsFuture Gener Comput Syst201997849872 – reference: HollandJHGenetic algorithmsSci Am199226716672 – reference: MirjaliliSMLewisAThe whale optimization algorithmAdv Eng Softw2016955167 – reference: ČrepinšekMLiuS-HMernikMExploration and exploitation in evolutionary algorithms: a surveyACM Comput Surv20134531351293.68251 – reference: Neggaz N, Houssein EH, Hussain K (2020) An efficient henry gas solubility optimization for feature selection. Exp Syst Appl 113364 – reference: HousseinEHHosneyMEOlivaDMohamedWMHassaballahMA novel hybrid Harris hawks optimization and support vector machines for drug design and discoveryComput Chem Eng2020133106656 – reference: LiuS-HMernikMHrnčičDČrepinšekMA parameter control method of evolutionary algorithms using exploration and exploitation measures with a practical application for fitting sovova’s mass transfer modelAppl Soft Comput201313937923805 – reference: RorresCCompleting book ii of archimedes’s on floating bodiesMath Intell2004263324220880131069.01004 – reference: ChengSShiYQinQZhangQBaiRPopulation diversity maintenance in brain storm optimization algorithmJ Artif Intell Soft Comput Res2014428397 – reference: Dorigo M, Di Caro G (1999) Ant colony optimization: a new meta-heuristic. In: Proceedings of the 1999 congress on evolutionary computation, 1999 CEC 99, pp 1470–1477 – reference: JavidyBHatamlouAMirjaliliSIons motion algorithm for solving optimization problemsAppl Soft Comput2015327279 – reference: ZhaoWWangLAn effective bacterial foraging optimizer for global optimizationInf Sci2016329719735 – reference: HussainKSallehMNMChengSShiYOn the exploration and exploitation in popular swarm-based metaheuristic algorithmsNeural Comput Appl2018311176657683 – reference: KavehAShareMAMMoslehiMMagnetic charged system search: a new meta-heuristic algorithm for optimizationActa Mech20132241851071318.78011 – reference: RorresCAcross neighborhood search for numerical optimizationInf Sci2016329597618 – ident: 1893_CR49 doi: 10.1007/11579427_66 – ident: 1893_CR14 doi: 10.1109/CEC.1999.782657 – volume: 116 start-page: 405 issue: 2 year: 1994 ident: 1893_CR50 publication-title: J Mech Des doi: 10.1115/1.2919393 – ident: 1893_CR6 doi: 10.1016/j.eswa.2020.113364 – volume: 94 start-page: 103731 year: 2020 ident: 1893_CR3 publication-title: Eng Appl Artif Intell doi: 10.1016/j.engappai.2020.103731 – volume: 13 start-page: 3792 issue: 9 year: 2013 ident: 1893_CR21 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2013.05.010 – volume: 267 start-page: 66 issue: 1 year: 1992 ident: 1893_CR13 publication-title: Sci Am doi: 10.1038/scientificamerican0792-66 – volume: 89 start-page: 228 year: 2015 ident: 1893_CR18 publication-title: Knowl-Based Syst doi: 10.1016/j.knosys.2015.07.006 – volume: 112 start-page: 283 year: 2012 ident: 1893_CR24 publication-title: Comput Struct doi: 10.1016/j.compstruc.2012.09.003 – volume: 110 start-page: 69 year: 2017 ident: 1893_CR29 publication-title: Adv Eng Softw doi: 10.1016/j.advengsoft.2017.03.014 – volume: 31 start-page: 7665 issue: 11 year: 2018 ident: 1893_CR41 publication-title: Neural Comput Appl doi: 10.1007/s00521-018-3592-0 – volume: 52 start-page: 2191 issue: 4 year: 2019 ident: 1893_CR10 publication-title: Artif Intell Rev doi: 10.1007/s10462-017-9605-z – volume: 26 start-page: 32 issue: 3 year: 2004 ident: 1893_CR38 publication-title: Math Intell doi: 10.1007/BF02986750 – volume: 59 start-page: 20 year: 2016 ident: 1893_CR9 publication-title: Exp Syst Appl doi: 10.1016/j.eswa.2016.04.018 – volume: 41 start-page: 113 issue: 2 year: 2000 ident: 1893_CR47 publication-title: Comput Ind doi: 10.1016/S0166-3615(99)00046-9 – volume: 32 start-page: 10759 issue: 14 year: 2020 ident: 1893_CR7 publication-title: Neural Comput Appl doi: 10.1007/s00521-019-04611-0 – volume: 329 start-page: 597 year: 2016 ident: 1893_CR39 publication-title: Inf Sci doi: 10.1016/j.ins.2015.09.051 – volume: 96 start-page: 120 issue: 96 year: 2016 ident: 1893_CR27 publication-title: Knowl-Based Syst doi: 10.1016/j.knosys.2015.12.022 – volume: 179 start-page: 2232 issue: 13 year: 2009 ident: 1893_CR23 publication-title: Inf Sci doi: 10.1016/j.ins.2009.03.004 – volume: 497 start-page: 219 year: 2019 ident: 1893_CR2 publication-title: Appl Soft Comput – volume: 1 start-page: 67 issue: 1 year: 1997 ident: 1893_CR37 publication-title: IEEE Trans Evol Comput doi: 10.1109/4235.585893 – volume: 69 start-page: 46 year: 2014 ident: 1893_CR16 publication-title: Adv Eng Softw doi: 10.1016/j.advengsoft.2013.12.007 – volume: 42 start-page: 21 issue: 1 year: 2014 ident: 1893_CR15 publication-title: Artif Intell Rev doi: 10.1007/s10462-012-9328-0 – volume: 133 start-page: 106656 year: 2020 ident: 1893_CR5 publication-title: Comput Chem Eng doi: 10.1016/j.compchemeng.2019.106656 – volume: 329 start-page: 719 year: 2016 ident: 1893_CR17 publication-title: Inf Sci doi: 10.1016/j.ins.2015.10.001 – ident: 1893_CR8 doi: 10.1109/ICENCO.2017.8289778 – volume: 114 start-page: 163 year: 2017 ident: 1893_CR19 publication-title: Adv Eng Softw doi: 10.1016/j.advengsoft.2017.07.002 – volume: 110 start-page: 151 issue: 1 year: 2012 ident: 1893_CR45 publication-title: Comput Struct doi: 10.1016/j.compstruc.2012.07.010 – volume: 4 start-page: 227 issue: 3 year: 2018 ident: 1893_CR44 publication-title: Complex Intell Syst doi: 10.1007/s40747-018-0071-2 – volume: 224 start-page: 85 issue: 1 year: 2013 ident: 1893_CR33 publication-title: Acta Mech doi: 10.1007/s00707-012-0745-6 – volume: 45 start-page: 1 issue: 3 year: 2013 ident: 1893_CR42 publication-title: ACM Comput Surv doi: 10.1145/2480741.2480752 – volume: 95 start-page: 51 year: 2016 ident: 1893_CR20 publication-title: Adv Eng Softw doi: 10.1016/j.advengsoft.2016.01.008 – volume: 36 start-page: 315 year: 2015 ident: 1893_CR30 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2015.07.028 – volume: 33 start-page: 1 year: 2017 ident: 1893_CR36 publication-title: Swarm Evol Comput doi: 10.1016/j.swevo.2016.12.005 – volume: 89 start-page: 283 year: 2019 ident: 1893_CR31 publication-title: Knowl-Based Syst doi: 10.1016/j.knosys.2018.08.030 – ident: 1893_CR46 – volume: 4 start-page: 83 issue: 2 year: 2014 ident: 1893_CR40 publication-title: J Artif Intell Soft Comput Res doi: 10.1515/jaiscr-2015-0001 – volume: 3 start-page: 11 issue: 1 year: 2011 ident: 1893_CR43 publication-title: Int J Innov Comput Appl doi: 10.1504/IJICA.2011.037947 – volume: 220 start-page: 671 issue: 4598 year: 1983 ident: 1893_CR11 publication-title: Science doi: 10.1126/science.220.4598.671 – volume: 101 start-page: 646 year: 2019 ident: 1893_CR25 publication-title: Future Gener Comput Syst doi: 10.1016/j.future.2019.07.015 – volume: 75 start-page: 1 year: 2015 ident: 1893_CR28 publication-title: Knowl-Based Syst doi: 10.1016/j.knosys.2014.07.025 – volume: 191 start-page: 105190 year: 2020 ident: 1893_CR32 publication-title: Knowl-Based Syst doi: 10.1016/j.knosys.2019.105190 – volume: 13 start-page: 2592 issue: 5 year: 2013 ident: 1893_CR48 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2012.11.026 – ident: 1893_CR12 – volume: 213 start-page: 267 year: 2010 ident: 1893_CR22 publication-title: Acta Mech doi: 10.1007/s00707-009-0270-4 – volume: 14 start-page: 381 issue: 3 year: 2010 ident: 1893_CR26 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2009.2033580 – ident: 1893_CR1 doi: 10.1016/j.asoc.2020.106347 – volume: 97 start-page: 849 year: 2019 ident: 1893_CR4 publication-title: Future Gener Comput Syst doi: 10.1016/j.future.2019.02.028 – volume: 26 start-page: 8 year: 2016 ident: 1893_CR34 publication-title: Swarm Evol Comput doi: 10.1016/j.swevo.2015.07.002 – volume: 32 start-page: 72 year: 2015 ident: 1893_CR35 publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2015.03.035
SSID	ssj0003301
Score	2.702116
Snippet	The difficulty and complexity of the real-world numerical optimization problems has grown manifold, which demands efficient optimization methods. To date,...
SourceID	proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	1531
SubjectTerms	Artificial Intelligence Complexity Computer Science Design engineering Evolutionary computation Genetic algorithms Heuristic methods Machines Manufacturing Mechanical Engineering Optimization algorithms Particle swarm optimization Performance evaluation Processes Software testing Source code Trigonometric functions
SummonAdditionalLinks	– databaseName: SpringerLINK Contemporary 1997-Present dbid: RSV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LSwMxEB60evBifWK1Sg7eNLDvZL2JWDyIiC96W_JaW-hDulsP_fUmabZrRQU9JxvCZCbfzGbmG4DT2KdKkpBjqX1VHHHpYSZMsMI95SsW-rmwXUtuyd0d7XbTe1cUVlTZ7tWTpL2pPxW7RSa9JzCJVBpl8WwV1jTcUWOOD48vi_tXR-i2T56OLHCSpF1XKvP9GstwVPuYX55FLdp0mv_b5xZsOu8SXc7VYRtW1GgHmlXnBuQMeRe4JZzVQKgKNNaXxtBVYyI2eB1P-mVveIEY0h43GqqS9dR0zudcDyPt6yKttuZ3xPIKrkNNsQfPneunqxvsui1gEdK4xNRAvUxIGgiuD8kTQnEvDhjjhMaUe1KFPM1NbSqT2u2jkhKSe3lOKBcp1Xa8D43ReKQOAOWRxzQ2MkMkFJGIsTxNdLSqfE9FiUxpC_xK6JlwVOSmI8Ygq0mUjRAzLcTMCjGbteBs8c3bnIjj19nt6iwzZ5RFFkSGfs-UbbXgvDq7evjn1Q7_Nv0INgKT-WIz1drQKCdTdQzr4r3sF5MTq6wf07Hmaw priority: 102 providerName: Springer Nature
Title	Archimedes optimization algorithm: a new metaheuristic algorithm for solving optimization problems
URI	https://link.springer.com/article/10.1007/s10489-020-01893-z https://www.proquest.com/docview/2487630319
Volume	51
WOSCitedRecordID	wos000573749800001&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: PRVAVX databaseName: Springer Journals customDbUrl: eissn: 1573-7497 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0003301 issn: 0924-669X databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LT9wwEB6Vx4FLaaFVl9KVD9zAwskmsdNLRRGoUmG1gha2vUR-pVRid4GEHvj1zGQdIpDKhctcnIyizHge9sx8AFtppLyTA8Mdxqo8MU5wbSlZMcJHXg-i0jaoJUdyOFTjcT4KB25VKKtsbWJjqN3M0hn5bpzQ7DTquflydc0JNYpuVwOExgIsRXEckZ5_l_zBEmOu3iDmYY7Bsywfh6aZ0DqXULFQTGVZ6LP53WPH1EWbTy5IG79zuPrSL34Dr0PEyfbmKvIWXvnpGqy2aA4sbO51MM0QWnSOvmIzNCST0KHJ9OUfZFtfTD4zzTAKZxNf6wt_O5_x3C0zjH8ZqjIdUTzmEFBrqnfw8_Dgx_43HhAYuB2otOaK3L_LZB5bg4IT1noj0lhrI1WqjHB-YPKS-lW1w1BQOSVlKcpSKmNzhXv7PSxOZ1P_AViZCI3-UtNwoUQmWpd5hhmsj4RPMperHkTt7y9sGE9OKBmXRTdYmURWoMiKRmTFXQ-2H965mg_nePbpzVZORdioVdEJqQc7raS75f9z23ie20dYian6palW24TF-ubWf4Jl-6_-W930YUGe_-rD0teD4eik3ygt0mOxT1SeIh2lv5GenJ7dAwC89dw
linkProvider	ProQuest
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3NT9RAFH-B1QQvIiJxFWUOeMKJ03a2nZoYY1ACYd1wwGRvZb4KJuwu0q5G_ij_Rt_rTmkwkRsHzm1fZjq_eR8z770fwPYgUt5lieEOfVUujRNcWwpWjPCR10lU2oa1ZJiNRmo8zo-W4E9bC0Npla1ObBS1m1k6I38XS-qdRjU3Hy9-cGKNotvVlkJjAYtD__sXhmzVh4PPuL5v4njvy_HuPg-sAtwmalBzRSbNpVkeW4ODEdZ6Iwax1iZTA2WE84nJS6rB1A7dG-VUlpWiLDNlbK4Qryh3GR5IiWOhVEGxe635k6ShWxYY0_A0zcehSCeU6klKToopDQx9BH510xB23u0_F7KNndtbvW9_6Ak8Dh41-7TYAmuw5KdPYbVlq2BBea2DaZrsovH3FZuhopyEClSmz09xGvXZ5D3TDKMMNvG1PvPzRQ_r7jFD_57hVqUjmJsSAitP9Qy-3clMN6A3nU39c2ClFBr9AU3Nk2QmtS7zFCN0HwkvU5erPkTtchc2tF8nFpDzomscTRApECJFA5Hiqg87199cLJqP3Pr2ZouLIiiiquhA0Ye3LbK6x_-X9uJ2aVuwsn_8dVgMD0aHL-FRTJk-TWbeJvTqy7l_BQ_tz_p7dfm62SIMTu4acX8B8-xNAg
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LTxRBEK4gGuNFfBEXUPsAJ-3Q8-weE2MMuJEs2XDQZG9jvwZI2F1gBo38NH6dVbM9TCCRGwfPPVOZnv66Ht1V9QFsZpHyTiaGO_RVeWqc4NpSsGKEj7xOosq2rCX7cjxWk0lxsARXXS0MpVV2OrFV1G5u6Yx8O06pdxrV3GxXIS3iYHf4-fSME4MU3bR2dBoLiIz8n98YvtWf9nZxrbfiePj1-843HhgGuE1U1nBF5s3lsoitwQ8T1nojslhrI1WmjHA-MUVF9ZjaoaujnJKyElUllbGFQuyi3AfwEK1wRntsJPm1FUiSlnpZYHzD87yYhIKdULaXUqJSTClh6C_wy5tGsfd0b13OtjZvuPI__61n8DR42uzLYms8hyU_ewErHYsFC0rtJZi2-S46Bb5mc1Sg01CZyvTJIU6jOZp-ZJph9MGmvtFH_mLR27ofZuj3M9zCdDRzU0Jg66lfwY97mekqLM_mM_8aWJUKjX6CpqZKqUy1roocI3cfCZ_mrlADiLqlL21oy07sICdl31Ca4FIiXMoWLuXlAN5fv3O6aEpy59MbHUbKoKDqsgfIAD50KOuH_y1t7W5p7-AxAq3c3xuP1uFJTAlAbcLeBiw35xf-DTyyv5rj-vxtu1sY_LxvwP0FTSVVqA
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=Archimedes+optimization+algorithm%3A+a+new+metaheuristic+algorithm+for+solving+optimization+problems&rft.jtitle=Applied+intelligence+%28Dordrecht%2C+Netherlands%29&rft.au=Hashim%2C+Fatma+A&rft.au=Hussain+Kashif&rft.au=Houssein%2C+Essam+H&rft.au=Mabrouk%2C+Mai+S&rft.date=2021-03-01&rft.pub=Springer+Nature+B.V&rft.issn=0924-669X&rft.eissn=1573-7497&rft.volume=51&rft.issue=3&rft.spage=1531&rft.epage=1551&rft_id=info:doi/10.1007%2Fs10489-020-01893-z&rft.externalDBID=HAS_PDF_LINK
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0924-669X&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0924-669X&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0924-669X&client=summon