Chaotic whale optimization algorithm
Graphical abstract Graphical Abstract AbstractThe Whale Optimization Algorithm (WOA) is a recently developed meta-heuristic optimization algorithm which is based on the hunting mechanism of humpback whales. Similarly to other meta-heuristic algorithms, the main problem faced by WOA is slow convergen...
Saved in:
| Published in: | Journal of computational design and engineering Vol. 5; no. 3; pp. 275 - 284 |
|---|---|
| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Oxford University Press
01.07.2018
한국CDE학회 |
| Subjects: | |
| ISSN: | 2288-5048, 2288-4300, 2288-5048 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Graphical abstract
Graphical Abstract
AbstractThe Whale Optimization Algorithm (WOA) is a recently developed meta-heuristic optimization algorithm which is based on the hunting mechanism of humpback whales. Similarly to other meta-heuristic algorithms, the main problem faced by WOA is slow convergence speed. So to enhance the global convergence speed and to get better performance, this paper introduces chaos theory into WOA optimization process. Various chaotic maps are considered in the proposed chaotic WOA (CWOA) methods for tuning the main parameter of WOA which helps in controlling exploration and exploitation. The proposed CWOA methods are benchmarked on twenty well-known test functions. The results prove that the chaotic maps (especially Tent map) are able to improve the performance of WOA.
Highlights
Chaos has been introduced into WOA to improve its performance.Ten chaotic maps have been investigated to tune the key parameter ‘ p’ of WOA.The proposed CWOA is validated on a set of twenty benchmark functions.The proposed CWOA is validated on a set of twenty benchmark functions.Statistical results suggest that CWOA has better reliability of global optimality. |
|---|---|
| AbstractList | Graphical abstract
Graphical Abstract
AbstractThe Whale Optimization Algorithm (WOA) is a recently developed meta-heuristic optimization algorithm which is based on the hunting mechanism of humpback whales. Similarly to other meta-heuristic algorithms, the main problem faced by WOA is slow convergence speed. So to enhance the global convergence speed and to get better performance, this paper introduces chaos theory into WOA optimization process. Various chaotic maps are considered in the proposed chaotic WOA (CWOA) methods for tuning the main parameter of WOA which helps in controlling exploration and exploitation. The proposed CWOA methods are benchmarked on twenty well-known test functions. The results prove that the chaotic maps (especially Tent map) are able to improve the performance of WOA.
Highlights
Chaos has been introduced into WOA to improve its performance.Ten chaotic maps have been investigated to tune the key parameter ‘ p’ of WOA.The proposed CWOA is validated on a set of twenty benchmark functions.The proposed CWOA is validated on a set of twenty benchmark functions.Statistical results suggest that CWOA has better reliability of global optimality. The Whale Optimization Algorithm (WOA) is a recently developed meta-heuristic optimization algorithm which is based on the hunting mechanism of humpback whales. Similarly to other meta-heuristic algorithms, the main problem faced by WOA is slow convergence speed. So to enhance the global convergence speed and to get better performance, this paper introduces chaos theory into WOA optimization process. Various chaotic maps are considered in the proposed chaotic WOA (CWOA) methods for tuning the main parameter of WOA which helps in controlling exploration and exploitation. The proposed CWOA methods are benchmarked on twenty well-known test functions. The results prove that the chaotic maps (especially Tent map) are able to improve the performance of WOA. The Whale Optimization Algorithm (WOA) is a recently developed meta-heuristic optimization algorithm which is based on the hunting mechanism of humpback whales. Similarly to other meta-heuristic algo-rithms, the main problem faced by WOA is slow convergence speed. So to enhance the global conver-gence speed and to get better performance, this paper introduces chaos theory into WOA optimization process. Various chaotic maps are considered in the proposed chaotic WOA (CWOA) methods for tuning the main parameter of WOA which helps in controlling exploration and exploitation. The proposed CWOA methods are benchmarked on twenty well-known test functions. The results prove that the chaotic maps (especially Tent map) are able to improve the performance of WOA. KCI Citation Count: 128 The Whale Optimization Algorithm (WOA) is a recently developed meta-heuristic optimization algorithm which is based on the hunting mechanism of humpback whales. Similarly to other meta-heuristic algorithms, the main problem faced by WOA is slow convergence speed. So to enhance the global convergence speed and to get better performance, this paper introduces chaos theory into WOA optimization process. Various chaotic maps are considered in the proposed chaotic WOA (CWOA) methods for tuning the main parameter of WOA which helps in controlling exploration and exploitation. The proposed CWOA methods are benchmarked on twenty well-known test functions. The results prove that the chaotic maps (especially Tent map) are able to improve the performance of WOA. Highlights Chaos has been introduced into WOA to improve its performance. Ten chaotic maps have been investigated to tune the key parameter ‘ p’ of WOA. The proposed CWOA is validated on a set of twenty benchmark functions. The proposed CWOA is validated on a set of twenty benchmark functions. Statistical results suggest that CWOA has better reliability of global optimality. |
| Author | Arora, Sankalap Kaur, Gaganpreet |
| Author_xml | – sequence: 1 givenname: Gaganpreet surname: Kaur fullname: Kaur, Gaganpreet email: gaganpreet1292@gmail.com organization: DAV University, Jalandhar, Punjab, India – sequence: 2 givenname: Sankalap surname: Arora fullname: Arora, Sankalap email: sankalap.arora@gmail.com organization: DAV University, Jalandhar, Punjab, India |
| BackLink | https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002363895$$DAccess content in National Research Foundation of Korea (NRF) |
| BookMark | eNqNkD1PwzAQhi1UJErpH2DqAANDgn2x8zFWFR-FSpVQmU-uk7RO07hyjBD8epyGATEgpveG5z3dPedk0JimIOSS0ZBRFt9WYaXyIgTKkpBBSGl8QoYAaRoIytPBj_mMjNu2otSTEFGWDcnVbCuN02ryvpV1MTEHp_f6UzptmomsN8Zqt91fkNNS1m0x_s4Reb2_W80eg8XyYT6bLgIlGLhA8UgkFCJQZZIVQolEchEDzTMONM5lnoBaRzxlUpQKRExlIXIhklyqSHJYRyNy0-9tbIk7pdFIfcyNwZ3F6ctqjpHwl_PYs9c9u9Ot09jkbY1P0-elt5ACZLFIEyaAey7tOWVN29qiRKXd8T9npa6RUewkYoWdROwkIgP0En0VflUPVu-l_fi7FPQl83b4D_8FcPaCkg |
| CitedBy_id | crossref_primary_10_1080_13588265_2022_2074705 crossref_primary_10_1109_ACCESS_2024_3379149 crossref_primary_10_1080_0952813X_2022_2135613 crossref_primary_10_1080_15325008_2019_1602687 crossref_primary_10_1007_s11227_021_03626_6 crossref_primary_10_1007_s11771_023_5503_5 crossref_primary_10_1007_s41870_019_00346_2 crossref_primary_10_1007_s13369_021_06136_y crossref_primary_10_3389_feart_2024_1445241 crossref_primary_10_1093_jcde_qwac075 crossref_primary_10_1007_s12206_023_1022_4 crossref_primary_10_1109_ACCESS_2020_3010127 crossref_primary_10_1109_ACCESS_2020_2998324 crossref_primary_10_1016_j_conengprac_2024_106078 crossref_primary_10_1080_10236198_2023_2203779 crossref_primary_10_1109_ACCESS_2019_2905009 crossref_primary_10_1063_5_0217697 crossref_primary_10_1016_j_eswa_2021_114841 crossref_primary_10_1080_10739149_2023_2286366 crossref_primary_10_1177_16878140211051220 crossref_primary_10_1109_ACCESS_2022_3143802 crossref_primary_10_1002_ima_22888 crossref_primary_10_1109_ACCESS_2025_3573376 crossref_primary_10_1007_s10586_024_04628_8 crossref_primary_10_1002_2050_7038_12188 crossref_primary_10_1016_j_cie_2020_107086 crossref_primary_10_1093_jcde_qwab082 crossref_primary_10_1155_2022_9159130 crossref_primary_10_1007_s12652_021_03151_7 crossref_primary_10_1007_s12652_021_03234_5 crossref_primary_10_1016_j_ref_2020_06_008 crossref_primary_10_1002_2050_7038_12159 crossref_primary_10_55195_jscai_1503982 crossref_primary_10_1007_s00366_019_00917_8 crossref_primary_10_1007_s10489_024_05537_4 crossref_primary_10_1007_s12652_021_03136_6 crossref_primary_10_1016_j_scs_2021_102858 crossref_primary_10_1002_2050_7038_13124 crossref_primary_10_1038_s41598_025_86757_7 crossref_primary_10_1007_s42235_021_0041_z crossref_primary_10_1088_1742_6596_1684_1_012075 crossref_primary_10_1016_j_asoc_2019_105938 crossref_primary_10_4018_IJDST_2020010105 crossref_primary_10_3934_math_2025316 crossref_primary_10_1155_2022_1036913 crossref_primary_10_1007_s10489_021_02686_8 crossref_primary_10_1108_COMPEL_07_2021_0231 crossref_primary_10_1109_ACCESS_2019_2932180 crossref_primary_10_1007_s00366_021_01409_4 crossref_primary_10_1016_j_eswa_2025_126750 crossref_primary_10_1155_2021_5517060 crossref_primary_10_1007_s12559_022_10099_z crossref_primary_10_1007_s00500_022_07257_8 crossref_primary_10_3233_JIFS_210842 crossref_primary_10_1007_s41870_024_01875_1 crossref_primary_10_1371_journal_pone_0260725 crossref_primary_10_1016_j_compbiomed_2023_107404 crossref_primary_10_1007_s12652_020_02849_4 crossref_primary_10_1007_s00500_023_08090_3 crossref_primary_10_1093_jcde_qwad002 crossref_primary_10_1155_2022_1457547 crossref_primary_10_3233_JIFS_201459 crossref_primary_10_1007_s10586_024_04446_y crossref_primary_10_1016_j_cogsys_2025_101373 crossref_primary_10_1002_ese3_1182 crossref_primary_10_1111_exsy_12779 crossref_primary_10_1155_2021_9974230 crossref_primary_10_1016_j_compbiomed_2022_105858 crossref_primary_10_1016_j_eswa_2021_115178 crossref_primary_10_32604_cmes_2022_019198 crossref_primary_10_1109_ACCESS_2020_2993580 crossref_primary_10_1080_02726343_2019_1675443 crossref_primary_10_1016_j_jocs_2018_12_005 crossref_primary_10_1177_1369433219875295 crossref_primary_10_1155_2022_1966054 crossref_primary_10_1007_s10462_021_10114_z crossref_primary_10_1007_s12065_023_00892_6 crossref_primary_10_1016_j_eswa_2025_129128 crossref_primary_10_1093_jcde_qwac023 crossref_primary_10_1109_ACCESS_2019_2905961 crossref_primary_10_1016_j_iswa_2025_200511 crossref_primary_10_1093_jcde_qwad110 crossref_primary_10_1109_ACCESS_2020_2976101 crossref_primary_10_7717_peerj_cs_2393 crossref_primary_10_1016_j_ijimpeng_2022_104424 crossref_primary_10_1080_21642583_2022_2140723 crossref_primary_10_1007_s10479_022_04849_3 crossref_primary_10_1016_j_eswa_2019_113134 crossref_primary_10_1109_TIM_2023_3331392 crossref_primary_10_1007_s11220_020_00283_6 crossref_primary_10_1109_ACCESS_2020_2982441 crossref_primary_10_1080_02564602_2020_1843554 crossref_primary_10_1088_1402_4896_add8c7 crossref_primary_10_1093_jcde_qwac014 crossref_primary_10_1002_cpe_5949 crossref_primary_10_1088_1361_6501_abf8ed crossref_primary_10_1002_er_7928 crossref_primary_10_32604_cmc_2022_021719 crossref_primary_10_4018_IJAMC_2022010109 crossref_primary_10_1002_dac_4617 crossref_primary_10_1109_ACCESS_2024_3350336 crossref_primary_10_1007_s41403_025_00521_x crossref_primary_10_1016_j_enbuild_2023_113642 crossref_primary_10_4274_tjd_galenos_2024_73645 crossref_primary_10_1515_mt_2024_0151 crossref_primary_10_1109_ACCESS_2023_3265469 crossref_primary_10_1016_j_swevo_2019_03_004 crossref_primary_10_1038_s41598_024_56919_0 crossref_primary_10_1016_j_eswa_2025_127416 crossref_primary_10_1088_1674_1056_abf4fb crossref_primary_10_1371_journal_pone_0330324 crossref_primary_10_1155_2021_6315010 crossref_primary_10_1007_s00366_021_01487_4 crossref_primary_10_1109_ACCESS_2019_2895502 crossref_primary_10_1155_2021_3353926 crossref_primary_10_1016_j_cie_2019_106040 crossref_primary_10_1109_ACCESS_2019_2933661 crossref_primary_10_1155_2019_8718571 crossref_primary_10_1002_ett_4739 crossref_primary_10_1155_2021_6636813 crossref_primary_10_1093_jcde_qwac112 crossref_primary_10_1111_exsy_12719 crossref_primary_10_1093_jcde_qwac111 crossref_primary_10_1155_2021_5333278 crossref_primary_10_1109_ACCESS_2021_3067729 crossref_primary_10_1109_TVT_2020_2973294 crossref_primary_10_1109_ACCESS_2019_2959949 crossref_primary_10_1111_exsy_13146 crossref_primary_10_1109_JSEN_2024_3422995 crossref_primary_10_1016_j_knosys_2019_02_010 crossref_primary_10_3233_ICA_200641 crossref_primary_10_1109_ACCESS_2021_3073276 crossref_primary_10_1109_ACCESS_2021_3112742 crossref_primary_10_1080_0952813X_2022_2084566 crossref_primary_10_1002_tee_24223 crossref_primary_10_1080_0951192X_2020_1736717 crossref_primary_10_1007_s13748_021_00244_4 crossref_primary_10_21595_jme_2025_24805 crossref_primary_10_1002_tee_24205 crossref_primary_10_1007_s00521_022_08139_8 crossref_primary_10_1016_j_jcde_2019_02_002 crossref_primary_10_1007_s11276_022_03048_z crossref_primary_10_1007_s12065_022_00711_4 crossref_primary_10_1007_s41870_024_01791_4 crossref_primary_10_1108_COMPEL_12_2020_0422 crossref_primary_10_1007_s10696_023_09502_0 crossref_primary_10_1007_s42235_025_00674_z crossref_primary_10_1007_s13369_024_09222_z crossref_primary_10_1007_s00521_024_09461_z crossref_primary_10_1371_journal_pone_0279438 crossref_primary_10_1007_s13042_020_01252_x crossref_primary_10_1109_ACCESS_2020_3029728 crossref_primary_10_1111_exsy_12992 crossref_primary_10_7717_peerj_cs_1526 crossref_primary_10_1109_ACCESS_2022_3174854 crossref_primary_10_1007_s00500_021_05983_z crossref_primary_10_1049_gtd2_12019 crossref_primary_10_1155_2022_5129098 crossref_primary_10_1080_09720529_2021_2020421 crossref_primary_10_1007_s11227_021_04199_0 crossref_primary_10_32604_cmc_2023_037611 crossref_primary_10_1080_23311916_2020_1788876 crossref_primary_10_1002_jnm_2963 crossref_primary_10_1515_mt_2023_0319 crossref_primary_10_1080_0952813X_2020_1785020 crossref_primary_10_1109_ACCESS_2020_3044857 crossref_primary_10_1080_09720502_2021_2012892 crossref_primary_10_1007_s12652_021_03304_8 crossref_primary_10_1109_ACCESS_2020_2982988 crossref_primary_10_1002_aic_18115 crossref_primary_10_1177_01423312241274005 crossref_primary_10_1155_2022_9741278 crossref_primary_10_1007_s11227_023_05618_0 crossref_primary_10_1177_03019233251356091 crossref_primary_10_3389_fdata_2024_1422546 crossref_primary_10_1007_s11042_022_13462_2 crossref_primary_10_1016_j_procs_2023_01_128 crossref_primary_10_1109_ACCESS_2020_2988717 crossref_primary_10_32604_cmc_2022_026310 crossref_primary_10_1007_s11042_023_17329_y crossref_primary_10_1080_0952813X_2020_1785018 crossref_primary_10_1155_2021_5289038 crossref_primary_10_1080_01430750_2020_1860128 crossref_primary_10_1007_s00521_024_10815_w crossref_primary_10_1109_ACCESS_2023_3253432 crossref_primary_10_1016_j_eswa_2022_119421 crossref_primary_10_1051_jnwpu_20224040796 crossref_primary_10_1007_s12652_020_02762_w crossref_primary_10_1109_ACCESS_2019_2961811 crossref_primary_10_1007_s41870_023_01654_4 crossref_primary_10_1038_s41598_024_61578_2 crossref_primary_10_32604_cmes_2021_017310 crossref_primary_10_1108_ECAM_06_2024_0698 crossref_primary_10_1177_0954406220982641 crossref_primary_10_1186_s13638_021_02013_2 crossref_primary_10_1093_jcde_qwaf014 crossref_primary_10_1080_15325008_2020_1831653 crossref_primary_10_1007_s00202_023_02214_6 crossref_primary_10_1007_s10489_020_01881_3 crossref_primary_10_3233_JIFS_191747 crossref_primary_10_1093_jcde_qwac092 crossref_primary_10_1049_itr2_12555 crossref_primary_10_1109_JSYST_2021_3136208 crossref_primary_10_1080_15325008_2023_2240800 crossref_primary_10_1109_TGRS_2024_3370302 crossref_primary_10_3389_fevo_2023_1116083 crossref_primary_10_1155_2021_6611777 crossref_primary_10_1016_j_ifacol_2024_07_055 crossref_primary_10_3233_JIFS_236930 crossref_primary_10_18517_ijods_1_2_82_98_2020 crossref_primary_10_3233_JIFS_210781 crossref_primary_10_1002_ima_70036 crossref_primary_10_1016_j_asoc_2021_107451 crossref_primary_10_1007_s42235_023_00400_7 crossref_primary_10_1088_1742_6596_1213_3_032004 crossref_primary_10_1002_eng2_12381 crossref_primary_10_1109_ACCESS_2019_2929305 crossref_primary_10_1049_iet_sen_2019_0018 crossref_primary_10_1088_1402_4896_ad1377 crossref_primary_10_1002_oca_3021 crossref_primary_10_1007_s11831_022_09853_1 crossref_primary_10_1155_2022_3418269 crossref_primary_10_4018_IJSWIS_300824 crossref_primary_10_1002_ese3_1238 crossref_primary_10_1016_j_compbiomed_2022_105356 crossref_primary_10_23919_CJEE_2023_000032 |
| Cites_doi | 10.1007/s13369-017-2471-9 10.1109/81.933333 10.1109/4235.771163 10.1007/978-0-387-30164-8_630 10.1007/s10732-008-9080-4 10.1109/ISPCC.2015.7375029 10.1007/978-1-84882-983-1_15 10.1016/j.eswa.2007.02.002 10.1016/j.advengsoft.2016.01.008 10.1016/j.swevo.2011.02.002 10.1016/j.chaos.2004.11.095 10.1016/j.advengsoft.2013.12.007 10.1016/j.chaos.2006.04.057 10.1016/j.eswa.2010.02.042 10.1109/TEVC.2005.857610 10.1109/TEVC.2008.919004 10.1016/j.amc.2010.03.114 10.1016/j.jocs.2013.10.002 10.1016/S0166-3615(99)00046-9 10.1007/s00521-012-1028-9 10.1007/978-3-319-48012-1_4 10.1007/s00521-014-1597-x 10.3233/JIFS-16798 10.1016/j.advengsoft.2015.01.010 10.1016/j.cnsns.2012.05.010 10.1088/0253-6102/38/2/168 10.1186/s40807-017-0040-1 10.1016/j.cnsns.2012.06.009 10.1109/TEVC.2005.843751 10.1016/j.ins.2014.02.123 10.2307/3001968 10.1080/00207160108805080 10.1109/4235.585892 10.1103/PhysRevLett.64.821 10.1007/978-3-642-12538-6_6 |
| ContentType | Journal Article |
| Copyright | Society for Computational Design and Engineering 2017 |
| Copyright_xml | – notice: Society for Computational Design and Engineering 2017 |
| DBID | TOX AAYXX CITATION JDI ACYCR |
| DEWEY | 670.285 |
| DOI | 10.1016/j.jcde.2017.12.006 |
| DatabaseName | Oxford Academic Journals (Open Access) CrossRef KoreaScience Korean Citation Index |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | CrossRef |
| Database_xml | – sequence: 1 dbid: TOX name: Oxford Journals Open Access Collection url: https://academic.oup.com/journals/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Applied Sciences Engineering |
| DocumentTitleAlternate | Chaotic whale optimization algorithm |
| EISSN | 2288-5048 |
| EndPage | 284 |
| ExternalDocumentID | oai_kci_go_kr_ARTI_3523046 JAKO201822965871524 10_1016_j_jcde_2017_12_006 10.1016/j.jcde.2017.12.006 |
| GroupedDBID | .UV 0R~ 0SF 457 5VS 6I. AACTN AAEDT AAEDW AAFTH AAIKJ AALRI AAPXW AAVAP AAXUO ABEJV ABGNP ABMAC ABPTD ABXVV ACGFS ADBBV ADEZE ADVLN AEXQZ AFTJW AGHFR AITUG AKRWK ALMA_UNASSIGNED_HOLDINGS AMNDL AMRAJ BCNDV EBS EJD FDB GROUPED_DOAJ H13 IPNFZ JDI KQ8 KSI M41 M~E NCXOZ O9- OK1 RIG ROL ROX SSZ TOX AAYWO AAYXX ACVFH ADCNI AEUPX AFPUW AIGII AKBMS AKYEP CITATION IAO 4.4 FRF IGS ML0 OJZSN ABJCF ACYCR ADMLS AFKRA AZQEC BENPR BGLVJ CCPQU DWQXO GNUQQ HCIFZ ITC M7S PHGZM PHGZT PIMPY PMFND PTHSS |
| ID | FETCH-LOGICAL-c512t-c43570232cf79e5c57a45620d94206dad72cb3481a5fc2560ae5d557dac3a42b3 |
| ISICitedReferencesCount | 426 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000436871200001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2288-5048 2288-4300 |
| IngestDate | Sat May 31 03:24:03 EDT 2025 Fri Dec 22 11:58:34 EST 2023 Sat Nov 29 03:52:52 EST 2025 Tue Nov 18 21:41:34 EST 2025 Tue Jan 28 07:47:18 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 3 |
| Keywords | Chaos Whale Optimization Algorithm Meta-heuristic algorithm Chaotic maps |
| Language | English |
| License | This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). http://creativecommons.org/licenses/by-nc-nd/4.0 |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c512t-c43570232cf79e5c57a45620d94206dad72cb3481a5fc2560ae5d557dac3a42b3 |
| Notes | KISTI1.1003/JNL.JAKO201822965871524 |
| OpenAccessLink | http://dx.doi.org/10.1016/j.jcde.2017.12.006 |
| PageCount | 10 |
| ParticipantIDs | nrf_kci_oai_kci_go_kr_ARTI_3523046 kisti_ndsl_JAKO201822965871524 crossref_citationtrail_10_1016_j_jcde_2017_12_006 crossref_primary_10_1016_j_jcde_2017_12_006 oup_primary_10_1016_j_jcde_2017_12_006 |
| PublicationCentury | 2000 |
| PublicationDate | 2018-07-01 |
| PublicationDateYYYYMMDD | 2018-07-01 |
| PublicationDate_xml | – month: 07 year: 2018 text: 2018-07-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationTitle | Journal of computational design and engineering |
| PublicationTitleAlternate | Journal of computational design and engineering |
| PublicationYear | 2018 |
| Publisher | Oxford University Press 한국CDE학회 |
| Publisher_xml | – name: Oxford University Press – name: 한국CDE학회 |
| References | Gandomi (2020042823361839300_b0095) 2013; 18 Liang (2020042823361839300_b0160) 2006; 10 Dos Santos Coelho (2020042823361839300_b0065) 2008; 34 Aljarah (2020042823361839300_b0020) 2016 Gandomi (2020042823361839300_b0090) 2013; 22 Yang (2020042823361839300_b0260) 2010 Tsai (2020042823361839300_b0240) 2015; 6 Coello (2020042823361839300_b0040) 2000; 41 Gandomi (2020042823361839300_b0080) 2012; 17 Alba (2020042823361839300_b0015) 2005; 9 Eberhart (2020042823361839300_b0070) 1995 Mirjalili (2020042823361839300_b0195) 2014; 69 Arora (2020042823361839300_b0035) 2017; 42 Yang (2020042823361839300_b0255) 2010 Gandomi (2020042823361839300_b0085) 2014; 5 Liu (2020042823361839300_b0170) 2005; 25 Mafarja (2020042823361839300_b0175) 2017 Mirjalili (2020042823361839300_b0190) 2016; 95 Simon (2020042823361839300_b0220) 2008; 12 Yao (2020042823361839300_b0275) 1999; 3 Mirjalili (2020042823361839300_b0180) 2015; 83 Yang (2020042823361839300_b0265) 2010 Alatas (2020042823361839300_b0010) 2010; 37 Dorigo (2020042823361839300_b0055) 1999 Wilcoxon (2020042823361839300_b0250) 1945; 1 Shu-Chuan (2020042823361839300_b0215) 2006 García (2020042823361839300_b0105) 2009; 15 Kellert (2020042823361839300_b0145) 1994 Derrac (2020042823361839300_b0045) 2011; 1 Jadhav (2020042823361839300_b0125) 2017 Kohli (2020042823361839300_b0155) 2017 Saremi (2020042823361839300_b0210) 2014; 25 Sivanandam (2020042823361839300_b0225) 2007 Pecora (2020042823361839300_b0200) 1990; 64 Alatas (2020042823361839300_b0005) 2010; 216 Kennedy (2020042823361839300_b0150) 2011 Reddy (2020042823361839300_b0205) 2017; 4 Digalakis (2020042823361839300_b0050) 2001; 77 He (2020042823361839300_b0115) 2001; 48 Yang (2020042823361839300_b0270) 2007; 34 Wang (2020042823361839300_b0245) 2014; 274 Arora (2020042823361839300_b0025) 2015 Li-Jiang (2020042823361839300_b0165) 2002; 38 Dorigo (2020042823361839300_b0060) 1997; 1 Gao (2020042823361839300_b0100) 2010; 6 Arora (2020042823361839300_b0030) 2017; 32 Kaveh (2020042823361839300_b0140) 2017 |
| References_xml | – volume: 42 start-page: 3325 issue: 8 year: 2017 ident: 2020042823361839300_b0035 article-title: Node localization in wireless sensor networks using butterfly optimization algorithm publication-title: Arabian Journal for Science and Engineering doi: 10.1007/s13369-017-2471-9 – volume: 48 start-page: 900 issue: 7 year: 2001 ident: 2020042823361839300_b0115 article-title: Chaotic characteristics of a one-dimensional iterative map with infinite collapses publication-title: IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications doi: 10.1109/81.933333 – volume: 3 start-page: 82 issue: 2 year: 1999 ident: 2020042823361839300_b0275 article-title: Evolutionary programming made faster publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.771163 – start-page: 760 volume-title: Encyclopedia of machine learning year: 2011 ident: 2020042823361839300_b0150 doi: 10.1007/978-0-387-30164-8_630 – volume: 15 start-page: 617 issue: 6 year: 2009 ident: 2020042823361839300_b0105 article-title: A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: A case study on the CEC'2005 special session on real parameter optimization publication-title: Journal of Heuristics doi: 10.1007/s10732-008-9080-4 – start-page: 220 volume-title: 2015 International conference on signal processing, computing and control (ISPCC) year: 2015 ident: 2020042823361839300_b0025 doi: 10.1109/ISPCC.2015.7375029 – start-page: 209 volume-title: Research and development in intelligent systems XXVI year: 2010 ident: 2020042823361839300_b0260 doi: 10.1007/978-1-84882-983-1_15 – volume: 34 start-page: 1905 issue: 3 year: 2008 ident: 2020042823361839300_b0065 article-title: Use of chaotic sequences in a biologically inspired algorithm for engineering design optimization publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2007.02.002 – volume: 95 start-page: 51 year: 2016 ident: 2020042823361839300_b0190 article-title: The whale optimization algorithm publication-title: Advances in Engineering Software doi: 10.1016/j.advengsoft.2016.01.008 – volume: 1 start-page: 3 issue: 1 year: 2011 ident: 2020042823361839300_b0045 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 and Evolutionary Computation doi: 10.1016/j.swevo.2011.02.002 – volume-title: Alexandria Engineering Journal year: 2017 ident: 2020042823361839300_b0125 article-title: WGC: Hybridization of exponential grey wolf optimizer with whale optimization for data clustering – volume: 25 start-page: 1261 issue: 5 year: 2005 ident: 2020042823361839300_b0170 article-title: Improved particle swarm optimization combined with chaos publication-title: Chaos, Solitons & Fractals doi: 10.1016/j.chaos.2004.11.095 – volume: 69 start-page: 46 year: 2014 ident: 2020042823361839300_b0195 article-title: Grey wolf optimizer publication-title: Advances in Engineering Software doi: 10.1016/j.advengsoft.2013.12.007 – volume-title: Principles of soft computing year: 2007 ident: 2020042823361839300_b0225 – volume: 34 start-page: 1366 issue: 4 year: 2007 ident: 2020042823361839300_b0270 article-title: On the efficiency of chaos optimization algorithms for global optimization publication-title: Chaos, Solitons & Fractals doi: 10.1016/j.chaos.2006.04.057 – volume: 37 start-page: 5682 issue: 8 year: 2010 ident: 2020042823361839300_b0010 article-title: Chaotic bee colony algorithms for global numerical optimization publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2010.02.042 – volume-title: In the wake of chaos: Unpredictable order in dynamical systems year: 1994 ident: 2020042823361839300_b0145 – start-page: 1470 volume-title: CEC 99. Proceedings of the 1999 congress on evolutionary computation, 1999 year: 1999 ident: 2020042823361839300_b0055 – volume: 10 start-page: 281 issue: 3 year: 2006 ident: 2020042823361839300_b0160 article-title: Comprehensive learning particle swarm optimizer for global optimization of multimodal functions publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2005.857610 – volume: 12 start-page: 702 issue: 6 year: 2008 ident: 2020042823361839300_b0220 article-title: Biogeography-based optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2008.919004 – volume: 216 start-page: 2687 issue: 9 year: 2010 ident: 2020042823361839300_b0005 article-title: Chaotic harmony search algorithms publication-title: Applied Mathematics and Computation doi: 10.1016/j.amc.2010.03.114 – volume: 6 start-page: 1194 year: 2015 ident: 2020042823361839300_b0240 article-title: Improving swarm intelligence accuracy with cosine functions for evolved bat algorithm publication-title: Journal of Information Hiding and Multimedia Signal Processing – volume: 5 start-page: 224 issue: 2 year: 2014 ident: 2020042823361839300_b0085 article-title: Chaotic bat algorithm publication-title: Journal of Computational Science doi: 10.1016/j.jocs.2013.10.002 – volume: 41 start-page: 113 issue: 2 year: 2000 ident: 2020042823361839300_b0040 article-title: Use of a self-adaptive penalty approach for engineering optimization problems publication-title: Computers in Industry doi: 10.1016/S0166-3615(99)00046-9 – volume: 22 start-page: 1239 issue: 6 year: 2013 ident: 2020042823361839300_b0090 article-title: Bat algorithm for constrained optimization tasks publication-title: Neural Computing and Applications doi: 10.1007/s00521-012-1028-9 – start-page: 1942 volume-title: Proceedings of IEEE international conference on neural networks year: 1995 ident: 2020042823361839300_b0070 article-title: Particle swarm optimization – start-page: 47 volume-title: Applications of metaheuristic optimization algorithms in civil engineering year: 2017 ident: 2020042823361839300_b0140 doi: 10.1007/978-3-319-48012-1_4 – volume: 25 start-page: 1077 issue: 5 year: 2014 ident: 2020042823361839300_b0210 article-title: Biogeography-based optimisation with chaos publication-title: Neural Computing and Applications doi: 10.1007/s00521-014-1597-x – volume: 32 start-page: 1079 issue: 1 year: 2017 ident: 2020042823361839300_b0030 article-title: An improved butterfly optimization algorithm with chaos publication-title: Journal of Intelligent & Fuzzy Systems doi: 10.3233/JIFS-16798 – volume: 83 start-page: 80 year: 2015 ident: 2020042823361839300_b0180 article-title: The ant lion optimizer publication-title: Advances in Engineering Software doi: 10.1016/j.advengsoft.2015.01.010 – volume: 17 start-page: 4831 issue: 12 year: 2012 ident: 2020042823361839300_b0080 article-title: Krill herd: A new bio-inspired optimization algorithm publication-title: Communications in Nonlinear Science and Numerical Simulation doi: 10.1016/j.cnsns.2012.05.010 – volume-title: Journal of Computational Design and Engineering year: 2017 ident: 2020042823361839300_b0155 article-title: Chaotic grey wolf optimization algorithm for constrained optimization problems – volume: 38 start-page: 168 issue: 2 year: 2002 ident: 2020042823361839300_b0165 article-title: Application of chaos in genetic algorithms publication-title: Communications in Theoretical Physics doi: 10.1088/0253-6102/38/2/168 – volume: 4 start-page: 3 issue: 1 year: 2017 ident: 2020042823361839300_b0205 article-title: Whale optimization algorithm for optimal sizing of renewable resources for loss reduction in distribution systems publication-title: Renewables: Wind, Water, and Solar doi: 10.1186/s40807-017-0040-1 – start-page: 1 volume-title: Soft Computing year: 2016 ident: 2020042823361839300_b0020 article-title: Optimizing connection weights in neural networks using the whale optimization algorithm – volume: 18 start-page: 89 issue: 1 year: 2013 ident: 2020042823361839300_b0095 article-title: Firefly algorithm with chaos publication-title: Communications in Nonlinear Science and Numerical Simulation doi: 10.1016/j.cnsns.2012.06.009 – volume-title: Neurocomputing year: 2017 ident: 2020042823361839300_b0175 article-title: Hybrid whale optimization algorithm with simulated annealing for feature selection – volume-title: Nature-inspired metaheuristic algorithms year: 2010 ident: 2020042823361839300_b0255 – start-page: 854 volume-title: 9th Pacific Rim international conference on artificial intelligence, LNAI 4099 year: 2006 ident: 2020042823361839300_b0215 article-title: Cat swarm optimization' – volume: 9 start-page: 126 issue: 2 year: 2005 ident: 2020042823361839300_b0015 article-title: The exploration/exploitation tradeoff in dynamic cellular genetic algorithms publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2005.843751 – volume: 6 start-page: 4235 issue: 9 year: 2010 ident: 2020042823361839300_b0100 article-title: A modified harmony search method in constrained optimization publication-title: International Journal of Innovative Computing, Information and Control – volume: 274 start-page: 17 year: 2014 ident: 2020042823361839300_b0245 article-title: Chaotic krill herd algorithm publication-title: Information Sciences doi: 10.1016/j.ins.2014.02.123 – volume: 1 start-page: 80 issue: 6 year: 1945 ident: 2020042823361839300_b0250 article-title: Individual comparisons by ranking methods publication-title: Biometrics Bulletin doi: 10.2307/3001968 – volume: 77 start-page: 481 issue: 4 year: 2001 ident: 2020042823361839300_b0050 article-title: On benchmarking functions for genetic algorithms publication-title: International Journal of Computer Mathematics doi: 10.1080/00207160108805080 – volume: 1 start-page: 53 issue: 1 year: 1997 ident: 2020042823361839300_b0060 article-title: Ant colony system: A cooperative learning approach to the traveling salesman problem publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.585892 – volume: 64 start-page: 821 issue: 8 year: 1990 ident: 2020042823361839300_b0200 article-title: Synchronization in chaotic systems publication-title: Physical Review Letters doi: 10.1103/PhysRevLett.64.821 – start-page: 65 volume-title: Nature inspired cooperative strategies for optimization (NICSO 2010) year: 2010 ident: 2020042823361839300_b0265 article-title: A new metaheuristic bat-inspired algorithm doi: 10.1007/978-3-642-12538-6_6 |
| SSID | ssj0001723019 ssib053376903 |
| Score | 2.5837457 |
| Snippet | Graphical abstract
Graphical Abstract
AbstractThe Whale Optimization Algorithm (WOA) is a recently developed meta-heuristic optimization algorithm which is... The Whale Optimization Algorithm (WOA) is a recently developed meta-heuristic optimization algorithm which is based on the hunting mechanism of humpback... |
| SourceID | nrf kisti crossref oup |
| SourceType | Open Website Open Access Repository Enrichment Source Index Database Publisher |
| StartPage | 275 |
| SubjectTerms | 기계공학 |
| Title | Chaotic whale optimization algorithm |
| URI | http://click.ndsl.kr/servlet/LinkingDetailView?cn=JAKO201822965871524&dbt=JAKO&org_code=O481&site_code=SS1481&service_code=01 https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002363895 |
| Volume | 5 |
| WOSCitedRecordID | wos000436871200001&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 | |
| ispartofPNX | Journal of Computational Design and Engineering , 2018, 5(3), , pp.275-284 |
| journalDatabaseRights | – providerCode: PRVAON databaseName: Directory of Open Access Journals customDbUrl: eissn: 2288-5048 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001723019 issn: 2288-5048 databaseCode: DOA dateStart: 20150101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 2288-5048 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001723019 issn: 2288-5048 databaseCode: M~E dateStart: 20140101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre – providerCode: PRVASL databaseName: Oxford Journals Open Access Collection customDbUrl: eissn: 2288-5048 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001723019 issn: 2288-5048 databaseCode: TOX dateStart: 20140101 isFulltext: true titleUrlDefault: https://academic.oup.com/journals/ providerName: Oxford University Press |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwELdg4wEeBgwmykcVoYmXKihx4jp-nCa-0YZEkfpmOeekn0uqtGP78zk7ThrGgPHAS1q5rZPcXS-_O59_R8jhMFGUayp8gBgDFDoEX6RcY8yTqlAHECbasut_5icnyXgsvrierWvbToAXRXJ5KVb_VdU4hso2W2f_Qd3tpDiA71HpeES14_FGij-eqtKwsF5MlSkcRJdw5vZaDtRyUlazzfTsN5AUbIuHJj2obXGHXV3ItqyFrYdW51bZ79REFSuztL21ndI2Lxp8VcVCLdWqm1kIk7YK1TkgSlG0cRTU6ybZdowFNTtm40FZx1Cirjesm6K4Byute8H94rPr9MH89Ry04S0Nuc3PBtcQZF95cLXlhB-PPp2aG6DUUNlwhCTxbbKLZxfGz41Ox42HQWzLh8KtO9ssHMcQzHZ_aW_W7ayqiwCvXtNP6GXXQPwZgpKiyuv9kR1oMnpA9pwCvaPaFh6SW4tyn9x38YXnvPd6n9zrkE8-IofOUDxrKF7XULzWUB6Tb2_fjI7f-65nhg8I3TY-IPzliMMo5FxkDBhXJsYNtIhpMNRKcwqp2XytWA4G7qqMaca4VhCpmKbRAdkpyiJ7QryQp5Bm-GEAIs5zitMxkcUcXXwMLFE9EjaykOAI5U1fk6VsKgfn0shPGvnJkEqUX48M2t-sajqVP367b0UsC71eymu03CMvUfZyATNpaNLN66SUi0piMPhBRnbFA2d5haq5weme_u10z8jd7f_kOdnZVOfZC3IHvm9m66pv0zl9a28_APlLhZY |
| linkProvider | Oxford University Press |
| 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=Chaotic+whale+optimization+algorithm&rft.jtitle=Journal+of+computational+design+and+engineering&rft.au=Kaur%2C+Gaganpreet&rft.au=Arora%2C+Sankalap&rft.date=2018-07-01&rft.issn=2288-4300&rft.eissn=2288-5048&rft.volume=5&rft.issue=3&rft.spage=275&rft.epage=284&rft_id=info:doi/10.1016%2Fj.jcde.2017.12.006&rft.externalDBID=n%2Fa&rft.externalDocID=JAKO201822965871524 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2288-5048&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2288-5048&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2288-5048&client=summon |