A Multi-Strategy Whale Optimization Algorithm and Its Application
Whale Optimization Algorithm (WOA) is a key tool for solving complex engineering optimization problems, aiming at adjusting important parameters to satisfy constraints and optimal objectives. WOA has a simple structure, few parameters, high search capability, and easy implementation. However, it suf...
Saved in:
| Published in: | Engineering applications of artificial intelligence Vol. 108; p. 104558 |
|---|---|
| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01.02.2022
|
| Subjects: | |
| ISSN: | 0952-1976, 1873-6769 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Whale Optimization Algorithm (WOA) is a key tool for solving complex engineering optimization problems, aiming at adjusting important parameters to satisfy constraints and optimal objectives. WOA has a simple structure, few parameters, high search capability, and easy implementation. However, it suffers from the same problems as other metaheuristic algorithms of being prone to local optima and slow convergence, for which the Multi-Strategy Whale Optimization Algorithm (MSWOA) is proposed. Four strategies are introduced in MSWOA. Firstly, a highly randomized chaotic logistic map is used to generate a high-quality initial population. Secondly, exploitation and exploration are enhanced by setting adaptive weights and dynamic convergence factors. Further, a Lévy flight mechanism is introduced to maintain the population diversity in each iteration. Finally, the Evolutionary Population Dynamics (EPD) mechanism is introduced to improve the efficiency of search agents in finding the optimum. Another problem lies in the Semi-Supervised Extreme Learning Machine (SSELM) based on manifold regularization is an effective classification and regression model, but the random generation of input weights and hidden layer thresholds and the grid selection of hyperparameters lead to unsatisfactory classification performance. To this end, we developed the MSWOA-SSELM model, optimally selected the parameters of SSLEM using MSWOA, and applied it to logging layer recognition, which effectively improved the accuracy of logging interpretation. By comparing the experiments with 14 swarm intelligence algorithms on 18 benchmark test functions, the CEC2017 benchmark suite, and an engineering application problem, the experimental results show that MSWOA is significantly superior and effective in solving global optimization problems. Finally, the proposed MSWOA-SSELM is applied in three wells and outperforms other classification models in terms of Accuracy (ACC), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). It obtained the best results with 96.2567% ACC, MAE of 0.0749, and RMSE of 0.3870. |
|---|---|
| AbstractList | Whale Optimization Algorithm (WOA) is a key tool for solving complex engineering optimization problems, aiming at adjusting important parameters to satisfy constraints and optimal objectives. WOA has a simple structure, few parameters, high search capability, and easy implementation. However, it suffers from the same problems as other metaheuristic algorithms of being prone to local optima and slow convergence, for which the Multi-Strategy Whale Optimization Algorithm (MSWOA) is proposed. Four strategies are introduced in MSWOA. Firstly, a highly randomized chaotic logistic map is used to generate a high-quality initial population. Secondly, exploitation and exploration are enhanced by setting adaptive weights and dynamic convergence factors. Further, a Lévy flight mechanism is introduced to maintain the population diversity in each iteration. Finally, the Evolutionary Population Dynamics (EPD) mechanism is introduced to improve the efficiency of search agents in finding the optimum. Another problem lies in the Semi-Supervised Extreme Learning Machine (SSELM) based on manifold regularization is an effective classification and regression model, but the random generation of input weights and hidden layer thresholds and the grid selection of hyperparameters lead to unsatisfactory classification performance. To this end, we developed the MSWOA-SSELM model, optimally selected the parameters of SSLEM using MSWOA, and applied it to logging layer recognition, which effectively improved the accuracy of logging interpretation. By comparing the experiments with 14 swarm intelligence algorithms on 18 benchmark test functions, the CEC2017 benchmark suite, and an engineering application problem, the experimental results show that MSWOA is significantly superior and effective in solving global optimization problems. Finally, the proposed MSWOA-SSELM is applied in three wells and outperforms other classification models in terms of Accuracy (ACC), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). It obtained the best results with 96.2567% ACC, MAE of 0.0749, and RMSE of 0.3870. |
| ArticleNumber | 104558 |
| Author | Xia, Kewen Zhang, Jiangnan Wang, Li Feng, Yu Yang, Wenbiao Li, Tiejun Fan, Shurui |
| Author_xml | – sequence: 1 givenname: Wenbiao surname: Yang fullname: Yang, Wenbiao email: 201921902025@stu.hebut.edu.cn organization: School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China – sequence: 2 givenname: Kewen orcidid: 0000-0003-3968-481X surname: Xia fullname: Xia, Kewen email: kwxia@hebut.edu.cn organization: School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China – sequence: 3 givenname: Shurui surname: Fan fullname: Fan, Shurui email: fansr@hebut.edu.cn organization: School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China – sequence: 4 givenname: Li surname: Wang fullname: Wang, Li email: qhdzywl@hebut.edu.cn organization: School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China – sequence: 5 givenname: Tiejun surname: Li fullname: Li, Tiejun email: 1993076@hebut.edu.cn organization: School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, China – sequence: 6 givenname: Jiangnan surname: Zhang fullname: Zhang, Jiangnan email: 201911901007@stu.hebut.edu.cn organization: School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China – sequence: 7 givenname: Yu surname: Feng fullname: Feng, Yu email: 202021902013@stu.hebut.edu.cn organization: School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China |
| BookMark | eNqFkMtKAzEUhoNUsK2-guQFpuYySWbAhUPRWqh0oeIy5NY2ZTozJFGoT--01Y2brg6cw_fzn28EBk3bOABuMZpghPndduKateo65ScEEdwvc8aKCzDEhaAZF7wcgCEqGclwKfgVGMW4RQjRIudDUFXw5bNOPntNQSW33sOPjaodXHbJ7_y3Sr5tYFWv2-DTZgdVY-E8RVh1Xe3N8XoNLleqju7md47B-9Pj2_Q5Wyxn82m1yAzFJGVa4JxRpqlGgohCYV0grQWi3FFcGmuJsISynNKculI7xvqBNBeWlrxQhI7B_SnXhDbG4FbS-HRs0Df3tcRIHnTIrfzTIQ865ElHj_N_eBf8ToX9efDhBLr-uS_vgozGu8Y464MzSdrWn4v4AUfof1c |
| CitedBy_id | crossref_primary_10_1016_j_measurement_2025_116648 crossref_primary_10_3390_electronics13101842 crossref_primary_10_1007_s11356_023_29498_2 crossref_primary_10_3390_math11112415 crossref_primary_10_1016_j_isatra_2024_02_014 crossref_primary_10_1007_s42235_024_00493_8 crossref_primary_10_3390_a18030119 crossref_primary_10_1016_j_compag_2025_110846 crossref_primary_10_1016_j_enconman_2024_118974 crossref_primary_10_1371_journal_pone_0320913 crossref_primary_10_3390_act14080390 crossref_primary_10_3390_en17174300 crossref_primary_10_1007_s12665_022_10380_2 crossref_primary_10_3390_math11092079 crossref_primary_10_1007_s00521_024_10377_x crossref_primary_10_3390_biomimetics8080576 crossref_primary_10_3390_app14198624 crossref_primary_10_1007_s10712_024_09853_9 crossref_primary_10_1016_j_rineng_2025_107086 crossref_primary_10_1007_s42235_025_00675_y crossref_primary_10_1177_03019233251356091 crossref_primary_10_3390_math12182848 crossref_primary_10_3390_s25072054 crossref_primary_10_1007_s10489_024_06147_w crossref_primary_10_1016_j_asoc_2025_112788 crossref_primary_10_1016_j_eswa_2022_119303 crossref_primary_10_1190_geo2023_0657_1 crossref_primary_10_1016_j_jhydrol_2024_132596 crossref_primary_10_1038_s41598_023_30409_1 crossref_primary_10_1007_s10586_025_05273_5 crossref_primary_10_1007_s44196_025_00898_1 crossref_primary_10_1016_j_heliyon_2024_e38412 crossref_primary_10_1007_s42235_024_00545_z crossref_primary_10_3390_mi13081186 crossref_primary_10_3390_biomimetics10080526 crossref_primary_10_32604_cmc_2024_049582 crossref_primary_10_1007_s10586_024_04455_x crossref_primary_10_1007_s13296_023_00800_9 crossref_primary_10_3390_axioms11120725 crossref_primary_10_1093_jcde_qwad060 crossref_primary_10_1093_jcde_qwac092 crossref_primary_10_1016_j_chemolab_2022_104635 crossref_primary_10_3390_land13111731 crossref_primary_10_1007_s10586_024_04978_3 crossref_primary_10_3390_axioms12030252 crossref_primary_10_1371_journal_pone_0309741 crossref_primary_10_1007_s10462_025_11239_1 crossref_primary_10_1038_s41598_024_77517_0 crossref_primary_10_3390_axioms12070664 crossref_primary_10_3233_JIFS_236930 crossref_primary_10_3390_electronics14122371 crossref_primary_10_1007_s00500_023_09351_x crossref_primary_10_1016_j_compeleceng_2025_110330 crossref_primary_10_3389_fenvs_2023_1152296 crossref_primary_10_1016_j_asoc_2025_112838 crossref_primary_10_1007_s11540_024_09728_x crossref_primary_10_1007_s00521_023_08287_5 crossref_primary_10_1016_j_ins_2024_121714 crossref_primary_10_1016_j_matcom_2022_12_022 crossref_primary_10_1007_s10586_025_05391_0 crossref_primary_10_3390_rs15174134 crossref_primary_10_1007_s11042_022_13819_7 crossref_primary_10_1371_journal_pone_0322494 crossref_primary_10_1108_IDD_11_2022_0118 crossref_primary_10_3390_sym15122128 crossref_primary_10_3390_en17112559 crossref_primary_10_3390_biomimetics10070476 crossref_primary_10_1007_s12008_024_02078_5 crossref_primary_10_3390_machines13060497 crossref_primary_10_1371_journal_pone_0322058 crossref_primary_10_3390_sym17081295 crossref_primary_10_3934_math_2025316 crossref_primary_10_1007_s11227_025_07106_z crossref_primary_10_3390_a17050172 crossref_primary_10_1007_s11227_023_05263_7 crossref_primary_10_1007_s00500_023_09153_1 crossref_primary_10_1038_s41598_024_56919_0 |
| Cites_doi | 10.1016/j.asoc.2015.07.036 10.1016/j.asoc.2018.08.047 10.1016/j.asoc.2019.105925 10.1016/j.ins.2018.10.025 10.1016/j.physa.2020.124203 10.1016/j.eswa.2019.03.002 10.1016/j.jbi.2017.03.002 10.1103/PhysRevLett.59.381 10.1016/j.cie.2018.06.018 10.1016/j.knosys.2015.12.022 10.1016/j.advengsoft.2013.12.007 10.1007/s11036-018-1005-3 10.1007/s10898-007-9149-x 10.1016/j.advengsoft.2016.01.008 10.1007/s13369-014-1156-x 10.3390/a14040122 10.1016/j.knosys.2015.07.006 10.1016/j.eswa.2019.113018 10.1016/j.knosys.2018.11.024 10.1016/j.eswa.2017.07.043 10.1016/j.cnsns.2012.06.009 10.1016/j.eswa.2020.113917 10.1108/02644401211235834 10.1155/2017/8986917 10.3390/pr9081319 10.1007/s40815-020-00976-w 10.1016/j.enconman.2018.05.062 10.1016/j.cnsns.2012.05.010 10.1080/15325008.2020.1793830 10.1016/j.cma.2004.09.007 10.1080/03081070701303470 10.1007/s00500-019-04290-y 10.1186/s13638-020-01721-5 10.1109/LAWP.2015.2490103 10.1016/j.engappai.2006.03.003 10.1016/j.engappai.2019.03.021 10.1016/j.ijepes.2020.106492 10.1016/j.enconman.2019.112243 10.1007/s00500-018-3598-7 10.1108/IJICC-02-2014-0005 10.1016/j.asoc.2020.106241 |
| ContentType | Journal Article |
| Copyright | 2021 Elsevier Ltd |
| Copyright_xml | – notice: 2021 Elsevier Ltd |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.engappai.2021.104558 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Applied Sciences Computer Science |
| EISSN | 1873-6769 |
| ExternalDocumentID | 10_1016_j_engappai_2021_104558 S0952197621003997 |
| GroupedDBID | --K --M .DC .~1 0R~ 1B1 1~. 1~5 29G 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXUO AAYFN ABBOA ABMAC ABXDB ABYKQ ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADJOM ADMUD ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA GBOLZ HLZ HVGLF HZ~ IHE J1W JJJVA KOM LG9 LY7 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SBC SDF SDG SDP SES SET SEW SPC SPCBC SST SSV SSZ T5K TN5 UHS WUQ ZMT ~G- 9DU AATTM AAXKI AAYWO AAYXX ABJNI ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD |
| ID | FETCH-LOGICAL-c312t-b714535b3b07278a1b80bb7036e319cdd27d23543343e9be553e90b67d3968a23 |
| ISICitedReferencesCount | 91 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000753879900008&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0952-1976 |
| IngestDate | Tue Nov 18 21:07:22 EST 2025 Sat Nov 29 07:06:22 EST 2025 Fri Feb 23 02:41:39 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Evolutionary population dynamics Oil layer recognition Lévy flight mechanism Whale optimization algorithm Semi-supervised extreme learning machine |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c312t-b714535b3b07278a1b80bb7036e319cdd27d23543343e9be553e90b67d3968a23 |
| ORCID | 0000-0003-3968-481X |
| ParticipantIDs | crossref_citationtrail_10_1016_j_engappai_2021_104558 crossref_primary_10_1016_j_engappai_2021_104558 elsevier_sciencedirect_doi_10_1016_j_engappai_2021_104558 |
| PublicationCentury | 2000 |
| PublicationDate | February 2022 2022-02-00 |
| PublicationDateYYYYMMDD | 2022-02-01 |
| PublicationDate_xml | – month: 02 year: 2022 text: February 2022 |
| PublicationDecade | 2020 |
| PublicationTitle | Engineering applications of artificial intelligence |
| PublicationYear | 2022 |
| Publisher | Elsevier Ltd |
| Publisher_xml | – name: Elsevier Ltd |
| References | Chen, Yang, Heidari, Zhao (b12) 2020 Meshram, Ghorbani, Shamshirband, Karimi, Meshram (b33) 2019; 23 Al-Azza, Al-Jodah, Harackiewicz (b5) 2016 Naderi, Narimani, Pourakbari-Kasmaei, Cerna, Marzband, Lehtonen (b42) 2021 Mohammadzadeh, Hashemzadeh (b40) 2015; 37 Mirjalili, Lewis (b37) 2016 Colorni, A., Dorigo, M., Maniezzo, V., 1991. Distributed optimization by ant colonies. In: Proceedings of the First European Conference on Artificial Life. Poláková, Tvrdik, Bujok (b47) 2014 Kennedy, Eberhart (b27) 1995 Duan, Qiao (b18) 2014 Mirjalili, Mirjalili, Lewis (b39) 2014 Balootaki, Rahmani, Moeinkhah, Mohammadzadeh (b10) 2020 Abdel-Basset, Manogaran, El-Shahat, Mirjalili (b4) 2018 Lee, Geem (b29) 2005; 194 Gandomi, Alavi (b19) 2012; 17 Yang, Gandomi (b56) 2012 Awad, Ali, Suganthan, Liang, Qu (b6) 2016 Mezura-Montes, Coello (b34) 2008; 37 Valdez, Castillo, Melin (b54) 2021; 14 Deb, K., 0000, GeneAS: A Robust Optimal Design Technique for Mechanical Component Design. Huang, Song, Gupta, Wu (b23) 2014 Karaboga, Basturk (b26) 2007 Mirjalili (b35) 2015 Mohammadzadeh, Kumbasar (b41) 2020; 91 Gandomi, Yang, Talatahari, Alavi (b20) 2013; 18 Passino (b46) 2002 Olivas, Valdez, Melin, Sombra, Castillo (b45) 2019; 476 Mirjalili (b36) 2016; 96 Guo, Liu, Dai, Xu (b21) 2020 Naderi, Pourakbari-Kasmaei, Cerna, Lehtonen (b43) 2021; 125 Kohli, Arora (b28) 2018; 5 Sun, Wang (b51) 2017 Dhiman, Kaur (b16) 2019; 82 Zhou, Pang, Chen, Chou (b57) 2018; 123 Sandgren (b49) 1990 Abd Elaziz, Oliva, Xiong (b2) 2017; 90 Chen, Yang, Heidari, Zhao (b13) 2020; 154 Bak, Tang, Wiesenfeld (b9) 1987; 59 Subramanya, Talukdar (b50) 2014 Abdel-Basset, El-Shahat, El-henawy, Sangaiah, Ahmed (b3) 2018 Dhiman, Kumar (b17) 2019; 165 Huang, Zhou, Ding, Zhang (b24) 2012 Valdez (b53) 2020; 24 Tharwat, Moemen, Hassanien (b52) 2017 Rathore, Sangwan, Prakash, Adhikari, Kharel, Cao (b48) 2020 Bai, Xia, Lin, Wu (b8) 2017 He, Wang (b22) 2007; 20 Li, Sun, Tseng, Li (b30) 2019 Kannan, Kramer (b25) 1994 Bernal, Lagunes, Castillo, Soria, Valdez (b11) 2021; 23 Azizivahed, Arefi, Naderi, Narimani, Fathi, Narimani (b7) 2020; 48 Mirjalili, Lewis, Sadiq (b38) 2014; 39 Nadimi-Shahraki, Taghian, Mirjalili (b44) 2021; 166 Long, Cai, Jiao, Xu, Wu (b31) 2020; 203 Abd Elaziz, Oliva (b1) 2018 Yang, Deb (b55) 2009 Mahdavi, Fesanghary, Damangir (b32) 2007; 188 Nadimi-Shahraki (10.1016/j.engappai.2021.104558_b44) 2021; 166 Kohli (10.1016/j.engappai.2021.104558_b28) 2018; 5 Lee (10.1016/j.engappai.2021.104558_b29) 2005; 194 Kennedy (10.1016/j.engappai.2021.104558_b27) 1995 Mirjalili (10.1016/j.engappai.2021.104558_b39) 2014 Guo (10.1016/j.engappai.2021.104558_b21) 2020 Mohammadzadeh (10.1016/j.engappai.2021.104558_b40) 2015; 37 Mirjalili (10.1016/j.engappai.2021.104558_b35) 2015 Li (10.1016/j.engappai.2021.104558_b30) 2019 Yang (10.1016/j.engappai.2021.104558_b56) 2012 Abd Elaziz (10.1016/j.engappai.2021.104558_b2) 2017; 90 Yang (10.1016/j.engappai.2021.104558_b55) 2009 Gandomi (10.1016/j.engappai.2021.104558_b19) 2012; 17 Meshram (10.1016/j.engappai.2021.104558_b33) 2019; 23 Azizivahed (10.1016/j.engappai.2021.104558_b7) 2020; 48 Zhou (10.1016/j.engappai.2021.104558_b57) 2018; 123 Bai (10.1016/j.engappai.2021.104558_b8) 2017 Huang (10.1016/j.engappai.2021.104558_b24) 2012 Mezura-Montes (10.1016/j.engappai.2021.104558_b34) 2008; 37 10.1016/j.engappai.2021.104558_b15 10.1016/j.engappai.2021.104558_b14 Poláková (10.1016/j.engappai.2021.104558_b47) 2014 Dhiman (10.1016/j.engappai.2021.104558_b16) 2019; 82 Sun (10.1016/j.engappai.2021.104558_b51) 2017 Abdel-Basset (10.1016/j.engappai.2021.104558_b3) 2018 Naderi (10.1016/j.engappai.2021.104558_b43) 2021; 125 Long (10.1016/j.engappai.2021.104558_b31) 2020; 203 Duan (10.1016/j.engappai.2021.104558_b18) 2014 Bernal (10.1016/j.engappai.2021.104558_b11) 2021; 23 He (10.1016/j.engappai.2021.104558_b22) 2007; 20 Mahdavi (10.1016/j.engappai.2021.104558_b32) 2007; 188 Mirjalili (10.1016/j.engappai.2021.104558_b38) 2014; 39 Tharwat (10.1016/j.engappai.2021.104558_b52) 2017 Gandomi (10.1016/j.engappai.2021.104558_b20) 2013; 18 Passino (10.1016/j.engappai.2021.104558_b46) 2002 Abd Elaziz (10.1016/j.engappai.2021.104558_b1) 2018 Chen (10.1016/j.engappai.2021.104558_b13) 2020; 154 Al-Azza (10.1016/j.engappai.2021.104558_b5) 2016 Mohammadzadeh (10.1016/j.engappai.2021.104558_b41) 2020; 91 Rathore (10.1016/j.engappai.2021.104558_b48) 2020 Naderi (10.1016/j.engappai.2021.104558_b42) 2021 Abdel-Basset (10.1016/j.engappai.2021.104558_b4) 2018 Sandgren (10.1016/j.engappai.2021.104558_b49) 1990 Balootaki (10.1016/j.engappai.2021.104558_b10) 2020 Subramanya (10.1016/j.engappai.2021.104558_b50) 2014 Mirjalili (10.1016/j.engappai.2021.104558_b36) 2016; 96 Bak (10.1016/j.engappai.2021.104558_b9) 1987; 59 Olivas (10.1016/j.engappai.2021.104558_b45) 2019; 476 Valdez (10.1016/j.engappai.2021.104558_b53) 2020; 24 Awad (10.1016/j.engappai.2021.104558_b6) 2016 Dhiman (10.1016/j.engappai.2021.104558_b17) 2019; 165 Karaboga (10.1016/j.engappai.2021.104558_b26) 2007 Kannan (10.1016/j.engappai.2021.104558_b25) 1994 Valdez (10.1016/j.engappai.2021.104558_b54) 2021; 14 Chen (10.1016/j.engappai.2021.104558_b12) 2020 Huang (10.1016/j.engappai.2021.104558_b23) 2014 Mirjalili (10.1016/j.engappai.2021.104558_b37) 2016 |
| References_xml | – volume: 24 start-page: 215 year: 2020 end-page: 226 ident: b53 article-title: A review of optimization swarm intelligence-inspired algorithms with type-2 fuzzy logic parameter adaptation publication-title: Soft Comput. – year: 2019 ident: b30 article-title: Extreme learning machine optimized by whale optimization algorithm using insulated gate bipolar transistor module aging degree evaluation publication-title: Expert Syst. Appl. – year: 2017 ident: b8 article-title: Attribute reduction based on consistent covering rough set and its application publication-title: Complexity – year: 2020 ident: b10 article-title: On the synchronization and stabilization of fractional-order chaotic systems: Recent advances and future perspectives publication-title: Physica A – volume: 37 start-page: 204 year: 2015 end-page: 216 ident: b40 article-title: A new robust observer-based adaptive type-2 fuzzy control for a class of nonlinear systems publication-title: Appl. Soft Comput. – year: 2015 ident: b35 article-title: Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm publication-title: Knowl.-Based Syst. – year: 2014 ident: b23 article-title: Semi-supervised and unsupervised extreme learning machines publication-title: IEEE Trans. Cybern. – volume: 59 start-page: 381 year: 1987 end-page: 384 ident: b9 article-title: Self-organized criticality: An explanation of the 1/f noise publication-title: Phys. Rev. Lett. – volume: 203 year: 2020 ident: b31 article-title: A new hybrid algorithm based on grey wolf optimizer and cuckoo search for parameter extraction of solar photovoltaic models publication-title: Energy Convers. Manage. – volume: 123 start-page: 67 year: 2018 end-page: 81 ident: b57 article-title: A modified particle swarm optimization algorithm for a batch-processing machine scheduling problem with arbitrary release times and non-identical job sizes publication-title: Comput. Ind. Eng. – volume: 90 start-page: 484 year: 2017 end-page: 500 ident: b2 article-title: An improved opposition-based Sine cosine algorithm for global optimization publication-title: Expert Syst. Appl. – volume: 476 start-page: 159 year: 2019 end-page: 175 ident: b45 article-title: Interval type-2 fuzzy logic for dynamic parameter adaptation in a modified gravitational search algorithm publication-title: Inform. Sci. – year: 2021 ident: b42 article-title: State-of-the-art of optimal active and reactive power flow: A comprehensive review from various standpoints publication-title: Processes – volume: 39 start-page: 4683 year: 2014 end-page: 4697 ident: b38 article-title: Autonomous particles groups for particle swarm optimization publication-title: Arab. J. Sci. Eng. – year: 2020 ident: b48 article-title: Hybrid WGWO: whale grey wolf optimization-based novel energy-efficient clustering for EH-WSNs publication-title: Eurasip J. Wirel. Commun. Netw. – volume: 23 start-page: 10429 year: 2019 end-page: 10438 ident: b33 article-title: River flow prediction using hybrid PSOGSA algorithm based on feed-forward neural network publication-title: Soft Comput. – volume: 96 start-page: 120 year: 2016 end-page: 133 ident: b36 article-title: SCA: A Sine cosine algorithm for solving optimization problems publication-title: Knowl.-Based Syst. – volume: 14 year: 2021 ident: b54 article-title: Bio-inspired algorithms and its applications for optimization in fuzzy clustering publication-title: Algorithms – year: 2018 ident: b3 article-title: A novel whale optimization algorithm for cryptanalysis in Merkle-Hellman cryptosystem publication-title: Mob. Netw. Appl. – volume: 20 start-page: 89 year: 2007 end-page: 99 ident: b22 article-title: An effective co-evolutionary particle swarm optimization for constrained engineering design problems publication-title: Eng. Appl. Artif. Intell. – year: 2017 ident: b52 article-title: Classification of toxicity effects of biotransformed hepatic drugs using whale optimized support vector machines publication-title: J. Biomed. Inform. – year: 2016 ident: b5 article-title: Spider monkey optimization: A novel technique for antenna optimization publication-title: IEEE Antennas Wirel. Propag. Lett. – year: 2014 ident: b39 article-title: Grey wolf optimizer publication-title: Adv. Eng. Softw. – year: 2007 ident: b26 article-title: A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm publication-title: J. Global Optim. – volume: 166 year: 2021 ident: b44 article-title: An improved grey wolf optimizer for solving engineering problems publication-title: Expert Syst. Appl. – year: 2018 ident: b1 article-title: Parameter estimation of solar cells diode models by an improved opposition-based whale optimization algorithm publication-title: Energy Convers. Manage. – year: 2014 ident: b50 article-title: Graph-based semi-supervised learning publication-title: Synth. Lect. Artif. Intell. Mach. Learn. – volume: 82 start-page: 148 year: 2019 end-page: 174 ident: b16 article-title: STOA: A bio-inspired based optimization algorithm for industrial engineering problems publication-title: Eng. Appl. Artif. Intell. – volume: 188 start-page: 1567 year: 2007 end-page: 1579 ident: b32 article-title: An improved harmony search algorithm for solving optimization problems publication-title: Appl. Math. Comput. – volume: 194 start-page: 3902 year: 2005 end-page: 3933 ident: b29 article-title: A new meta-heuristic algorithm for continuous engineering optimization: Harmony search theory and practice publication-title: Comput. Methods Appl. Mech. Engrg. – year: 2012 ident: b56 article-title: Bat algorithm: A novel approach for global engineering optimization publication-title: Eng. Comput. (Swansea, Wales) – year: 2014 ident: b47 article-title: Controlled restart in differential evolution applied to CEC2014 benchmark functions publication-title: Proceedings of the 2014 IEEE Congress on Evolutionary Computation – volume: 91 year: 2020 ident: b41 article-title: A new fractional-order general type-2 fuzzy predictive control system and its application for glucose level regulation publication-title: Appl. Soft Comput. – volume: 125 year: 2021 ident: b43 article-title: A novel hybrid self-adaptive heuristic algorithm to handle single- and multi-objective optimal power flow problems publication-title: Int. J. Electr. Power Energy Syst. – volume: 165 start-page: 169 year: 2019 end-page: 196 ident: b17 article-title: Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems publication-title: Knowl.-Based Syst. – year: 2020 ident: b21 article-title: An improved whale optimization algorithm for forecasting water resources demand publication-title: Appl. Soft Comput. – volume: 23 start-page: 42 year: 2021 end-page: 57 ident: b11 article-title: Optimization of type-2 fuzzy logic controller design using the GSO and FA algorithms publication-title: Int. J. Fuzzy Syst. – reference: Deb, K., 0000, GeneAS: A Robust Optimal Design Technique for Mechanical Component Design. – year: 2009 ident: b55 article-title: Cuckoo search via Lévy flights publication-title: 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009 - Proceedings – reference: Colorni, A., Dorigo, M., Maniezzo, V., 1991. Distributed optimization by ant colonies. In: Proceedings of the First European Conference on Artificial Life. – year: 2016 ident: b6 article-title: Problem definitions and evaluation criteria for the CEC 2017 special session and competition on single objective real-parameter numerical optimization – volume: 17 start-page: 4831 year: 2012 end-page: 4845 ident: b19 article-title: Krill herd: A new bio-inspired optimization algorithm publication-title: Commun. Nonlinear Sci. Numer. Simul. – volume: 5 start-page: 458 year: 2018 end-page: 472 ident: b28 article-title: Chaotic grey wolf optimization algorithm for constrained optimization problems publication-title: J. Comput. Des. Eng. – year: 2012 ident: b24 article-title: Extreme learning machine for regression and multiclass classification publication-title: IEEE Trans. Syst. Man Cybern. B – year: 2017 ident: b51 article-title: Elman neural network soft-sensor model of conversion velocity in polymerization process optimized by chaos whale optimization algorithm publication-title: IEEE Access – year: 2014 ident: b18 article-title: Pigeon-inspired optimization: A new swarm intelligence optimizer for air robot path planning publication-title: Int. J. Intell. Comput. Cybern. – year: 1994 ident: b25 article-title: An augmented Lagrange multiplier based method for mixed integer discrete continuous optimization and its applications to mechanical design – volume: 37 start-page: 443 year: 2008 end-page: 473 ident: b34 article-title: An empirical study about the usefulness of evolution strategies to solve constrained optimization problems publication-title: Int. J. Gen. Syst. – year: 2016 ident: b37 article-title: The whale optimization algorithm publication-title: Adv. Eng. Softw. – volume: 154 year: 2020 ident: b13 article-title: An efficient double adaptive random spare reinforced whale optimization algorithm publication-title: Expert Syst. Appl. – year: 2018 ident: b4 article-title: Integrating the whale algorithm with tabu search for quadratic assignment problem: A new approach for locating hospital departments publication-title: Appl. Soft Comput. – volume: 18 start-page: 89 year: 2013 end-page: 98 ident: b20 article-title: Firefly algorithm with chaos publication-title: Commun. Nonlinear Sci. Numer. Simul. – year: 1995 ident: b27 article-title: Particle swarm optimization publication-title: IEEE International Conference on Neural Networks - Conference Proceedings – year: 2002 ident: b46 article-title: Biomimicry of bacterial foraging for distributed optimization and control publication-title: IEEE Control Syst. – year: 2020 ident: b12 article-title: An efficient double adaptive random spare reinforced whale optimization algorithm publication-title: Expert Syst. Appl. – volume: 48 start-page: 485 year: 2020 end-page: 500 ident: b7 article-title: An efficient hybrid approach to solve bi-objective multi-area dynamic economic emission dispatch problem publication-title: Electr. Power Compon. Syst. – year: 1990 ident: b49 article-title: Nonlinear Integer and Discrete Programming in Mechanical – volume: 37 start-page: 204 year: 2015 ident: 10.1016/j.engappai.2021.104558_b40 article-title: A new robust observer-based adaptive type-2 fuzzy control for a class of nonlinear systems publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.07.036 – year: 2018 ident: 10.1016/j.engappai.2021.104558_b4 article-title: Integrating the whale algorithm with tabu search for quadratic assignment problem: A new approach for locating hospital departments publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2018.08.047 – year: 2014 ident: 10.1016/j.engappai.2021.104558_b23 article-title: Semi-supervised and unsupervised extreme learning machines publication-title: IEEE Trans. Cybern. – volume: 5 start-page: 458 year: 2018 ident: 10.1016/j.engappai.2021.104558_b28 article-title: Chaotic grey wolf optimization algorithm for constrained optimization problems publication-title: J. Comput. Des. Eng. – year: 2020 ident: 10.1016/j.engappai.2021.104558_b21 article-title: An improved whale optimization algorithm for forecasting water resources demand publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2019.105925 – volume: 476 start-page: 159 year: 2019 ident: 10.1016/j.engappai.2021.104558_b45 article-title: Interval type-2 fuzzy logic for dynamic parameter adaptation in a modified gravitational search algorithm publication-title: Inform. Sci. doi: 10.1016/j.ins.2018.10.025 – year: 2020 ident: 10.1016/j.engappai.2021.104558_b10 article-title: On the synchronization and stabilization of fractional-order chaotic systems: Recent advances and future perspectives publication-title: Physica A doi: 10.1016/j.physa.2020.124203 – year: 2019 ident: 10.1016/j.engappai.2021.104558_b30 article-title: Extreme learning machine optimized by whale optimization algorithm using insulated gate bipolar transistor module aging degree evaluation publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2019.03.002 – year: 2017 ident: 10.1016/j.engappai.2021.104558_b52 article-title: Classification of toxicity effects of biotransformed hepatic drugs using whale optimized support vector machines publication-title: J. Biomed. Inform. doi: 10.1016/j.jbi.2017.03.002 – volume: 59 start-page: 381 year: 1987 ident: 10.1016/j.engappai.2021.104558_b9 article-title: Self-organized criticality: An explanation of the 1/f noise publication-title: Phys. Rev. Lett. doi: 10.1103/PhysRevLett.59.381 – volume: 123 start-page: 67 year: 2018 ident: 10.1016/j.engappai.2021.104558_b57 article-title: A modified particle swarm optimization algorithm for a batch-processing machine scheduling problem with arbitrary release times and non-identical job sizes publication-title: Comput. Ind. Eng. doi: 10.1016/j.cie.2018.06.018 – volume: 96 start-page: 120 year: 2016 ident: 10.1016/j.engappai.2021.104558_b36 article-title: SCA: A Sine cosine algorithm for solving optimization problems publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2015.12.022 – year: 2014 ident: 10.1016/j.engappai.2021.104558_b39 article-title: Grey wolf optimizer publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2013.12.007 – year: 2018 ident: 10.1016/j.engappai.2021.104558_b3 article-title: A novel whale optimization algorithm for cryptanalysis in Merkle-Hellman cryptosystem publication-title: Mob. Netw. Appl. doi: 10.1007/s11036-018-1005-3 – year: 1995 ident: 10.1016/j.engappai.2021.104558_b27 article-title: Particle swarm optimization – year: 2007 ident: 10.1016/j.engappai.2021.104558_b26 article-title: A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm publication-title: J. Global Optim. doi: 10.1007/s10898-007-9149-x – year: 2002 ident: 10.1016/j.engappai.2021.104558_b46 article-title: Biomimicry of bacterial foraging for distributed optimization and control publication-title: IEEE Control Syst. – year: 1990 ident: 10.1016/j.engappai.2021.104558_b49 – year: 2016 ident: 10.1016/j.engappai.2021.104558_b37 article-title: The whale optimization algorithm publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2016.01.008 – ident: 10.1016/j.engappai.2021.104558_b15 – volume: 39 start-page: 4683 year: 2014 ident: 10.1016/j.engappai.2021.104558_b38 article-title: Autonomous particles groups for particle swarm optimization publication-title: Arab. J. Sci. Eng. doi: 10.1007/s13369-014-1156-x – volume: 14 year: 2021 ident: 10.1016/j.engappai.2021.104558_b54 article-title: Bio-inspired algorithms and its applications for optimization in fuzzy clustering publication-title: Algorithms doi: 10.3390/a14040122 – year: 2015 ident: 10.1016/j.engappai.2021.104558_b35 article-title: Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2015.07.006 – year: 2020 ident: 10.1016/j.engappai.2021.104558_b12 article-title: An efficient double adaptive random spare reinforced whale optimization algorithm publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2019.113018 – volume: 165 start-page: 169 year: 2019 ident: 10.1016/j.engappai.2021.104558_b17 article-title: Seagull optimization algorithm: Theory and its applications for large-scale industrial engineering problems publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2018.11.024 – year: 2014 ident: 10.1016/j.engappai.2021.104558_b50 article-title: Graph-based semi-supervised learning publication-title: Synth. Lect. Artif. Intell. Mach. Learn. – year: 2009 ident: 10.1016/j.engappai.2021.104558_b55 article-title: Cuckoo search via Lévy flights – volume: 90 start-page: 484 year: 2017 ident: 10.1016/j.engappai.2021.104558_b2 article-title: An improved opposition-based Sine cosine algorithm for global optimization publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2017.07.043 – volume: 18 start-page: 89 year: 2013 ident: 10.1016/j.engappai.2021.104558_b20 article-title: Firefly algorithm with chaos publication-title: Commun. Nonlinear Sci. Numer. Simul. doi: 10.1016/j.cnsns.2012.06.009 – volume: 166 year: 2021 ident: 10.1016/j.engappai.2021.104558_b44 article-title: An improved grey wolf optimizer for solving engineering problems publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2020.113917 – year: 2012 ident: 10.1016/j.engappai.2021.104558_b56 article-title: Bat algorithm: A novel approach for global engineering optimization publication-title: Eng. Comput. (Swansea, Wales) doi: 10.1108/02644401211235834 – year: 2017 ident: 10.1016/j.engappai.2021.104558_b8 article-title: Attribute reduction based on consistent covering rough set and its application publication-title: Complexity doi: 10.1155/2017/8986917 – year: 2021 ident: 10.1016/j.engappai.2021.104558_b42 article-title: State-of-the-art of optimal active and reactive power flow: A comprehensive review from various standpoints publication-title: Processes doi: 10.3390/pr9081319 – ident: 10.1016/j.engappai.2021.104558_b14 – volume: 23 start-page: 42 year: 2021 ident: 10.1016/j.engappai.2021.104558_b11 article-title: Optimization of type-2 fuzzy logic controller design using the GSO and FA algorithms publication-title: Int. J. Fuzzy Syst. doi: 10.1007/s40815-020-00976-w – year: 1994 ident: 10.1016/j.engappai.2021.104558_b25 – year: 2018 ident: 10.1016/j.engappai.2021.104558_b1 article-title: Parameter estimation of solar cells diode models by an improved opposition-based whale optimization algorithm publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2018.05.062 – volume: 17 start-page: 4831 year: 2012 ident: 10.1016/j.engappai.2021.104558_b19 article-title: Krill herd: A new bio-inspired optimization algorithm publication-title: Commun. Nonlinear Sci. Numer. Simul. doi: 10.1016/j.cnsns.2012.05.010 – year: 2016 ident: 10.1016/j.engappai.2021.104558_b6 – volume: 154 year: 2020 ident: 10.1016/j.engappai.2021.104558_b13 article-title: An efficient double adaptive random spare reinforced whale optimization algorithm publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2019.113018 – volume: 48 start-page: 485 year: 2020 ident: 10.1016/j.engappai.2021.104558_b7 article-title: An efficient hybrid approach to solve bi-objective multi-area dynamic economic emission dispatch problem publication-title: Electr. Power Compon. Syst. doi: 10.1080/15325008.2020.1793830 – volume: 194 start-page: 3902 year: 2005 ident: 10.1016/j.engappai.2021.104558_b29 article-title: A new meta-heuristic algorithm for continuous engineering optimization: Harmony search theory and practice publication-title: Comput. Methods Appl. Mech. Engrg. doi: 10.1016/j.cma.2004.09.007 – volume: 188 start-page: 1567 year: 2007 ident: 10.1016/j.engappai.2021.104558_b32 article-title: An improved harmony search algorithm for solving optimization problems publication-title: Appl. Math. Comput. – volume: 37 start-page: 443 year: 2008 ident: 10.1016/j.engappai.2021.104558_b34 article-title: An empirical study about the usefulness of evolution strategies to solve constrained optimization problems publication-title: Int. J. Gen. Syst. doi: 10.1080/03081070701303470 – volume: 24 start-page: 215 year: 2020 ident: 10.1016/j.engappai.2021.104558_b53 article-title: A review of optimization swarm intelligence-inspired algorithms with type-2 fuzzy logic parameter adaptation publication-title: Soft Comput. doi: 10.1007/s00500-019-04290-y – year: 2020 ident: 10.1016/j.engappai.2021.104558_b48 article-title: Hybrid WGWO: whale grey wolf optimization-based novel energy-efficient clustering for EH-WSNs publication-title: Eurasip J. Wirel. Commun. Netw. doi: 10.1186/s13638-020-01721-5 – year: 2016 ident: 10.1016/j.engappai.2021.104558_b5 article-title: Spider monkey optimization: A novel technique for antenna optimization publication-title: IEEE Antennas Wirel. Propag. Lett. doi: 10.1109/LAWP.2015.2490103 – volume: 20 start-page: 89 year: 2007 ident: 10.1016/j.engappai.2021.104558_b22 article-title: An effective co-evolutionary particle swarm optimization for constrained engineering design problems publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2006.03.003 – volume: 82 start-page: 148 year: 2019 ident: 10.1016/j.engappai.2021.104558_b16 article-title: STOA: A bio-inspired based optimization algorithm for industrial engineering problems publication-title: Eng. Appl. Artif. Intell. doi: 10.1016/j.engappai.2019.03.021 – year: 2017 ident: 10.1016/j.engappai.2021.104558_b51 article-title: Elman neural network soft-sensor model of conversion velocity in polymerization process optimized by chaos whale optimization algorithm publication-title: IEEE Access – year: 2012 ident: 10.1016/j.engappai.2021.104558_b24 article-title: Extreme learning machine for regression and multiclass classification publication-title: IEEE Trans. Syst. Man Cybern. B – volume: 125 year: 2021 ident: 10.1016/j.engappai.2021.104558_b43 article-title: A novel hybrid self-adaptive heuristic algorithm to handle single- and multi-objective optimal power flow problems publication-title: Int. J. Electr. Power Energy Syst. doi: 10.1016/j.ijepes.2020.106492 – volume: 203 year: 2020 ident: 10.1016/j.engappai.2021.104558_b31 article-title: A new hybrid algorithm based on grey wolf optimizer and cuckoo search for parameter extraction of solar photovoltaic models publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2019.112243 – volume: 23 start-page: 10429 year: 2019 ident: 10.1016/j.engappai.2021.104558_b33 article-title: River flow prediction using hybrid PSOGSA algorithm based on feed-forward neural network publication-title: Soft Comput. doi: 10.1007/s00500-018-3598-7 – year: 2014 ident: 10.1016/j.engappai.2021.104558_b18 article-title: Pigeon-inspired optimization: A new swarm intelligence optimizer for air robot path planning publication-title: Int. J. Intell. Comput. Cybern. doi: 10.1108/IJICC-02-2014-0005 – year: 2014 ident: 10.1016/j.engappai.2021.104558_b47 article-title: Controlled restart in differential evolution applied to CEC2014 benchmark functions – volume: 91 year: 2020 ident: 10.1016/j.engappai.2021.104558_b41 article-title: A new fractional-order general type-2 fuzzy predictive control system and its application for glucose level regulation publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.106241 |
| SSID | ssj0003846 |
| Score | 2.588017 |
| Snippet | Whale Optimization Algorithm (WOA) is a key tool for solving complex engineering optimization problems, aiming at adjusting important parameters to satisfy... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 104558 |
| SubjectTerms | Evolutionary population dynamics Lévy flight mechanism Oil layer recognition Semi-supervised extreme learning machine Whale optimization algorithm |
| Title | A Multi-Strategy Whale Optimization Algorithm and Its Application |
| URI | https://dx.doi.org/10.1016/j.engappai.2021.104558 |
| Volume | 108 |
| WOSCitedRecordID | wos000753879900008&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1873-6769 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0003846 issn: 0952-1976 databaseCode: AIEXJ dateStart: 19950201 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9QwELZgy4EL5amWR-UDt8iQxHGdHKOqFS1VQaLQvUVx7HZTlWyVzUL77zt-JVmoVBDi4o1Gcpz1fBrPjOeB0FsZlvpyjpJEGG9VyYiAc5sokAvhqUhUZhz63w750VE6nWafXUjQwrQT4E2TXl1ll_-V1UADZuvU2b9gd_9SIMAzMB1GYDuMf8T4PDBJtcTVnb0OTmZwCASfQDZ8d0mXQX5xNm_rbmb7Y-x3C6uNVgObvLN-KFcYjO-6TfhAa-KMTNePUWHPXo44T_SJakRdzj15aqNzP6qfQxLanvPCzpbtsh5c_Hb-YT32TIBRG65EefQpM0N8kvU7xiTKuKt_baVuyinRsbYrYtnUe_hdxFtvw_k71ZzB_y5rsPHjSF9VM1sD_pfy2V_0gno9sG1D0Mb4fbQWc5alE7SW7-9OD_pzm6Y2rct_4Cif_PbVbldlRurJ8WP0yNkVOLd4eILuqeYpWnc2BnYSfAEk38bD056hPMeriMEGMXiMGNwjBgNiMCAGjxDzHH3d2z3e-UBcZw1S0SjuiOBRwigTVISgv6ZlJNJQCF2LTYFIrqSMuYwpSyhNqMqEYgx-QrHNJc220zKmL9CkmTdqA2HQb6WKpDoFzTUBdRkMBglGeyijKuIwbCLmN6moXNl53f3kovDxheeF39xCb25hN3cTve_nXdrCK3fOyDwPCqc-WrWwAOjcMfflP8x9hR4O6H-NJl27VG_Qg-pHVy_aLYeyG3cElp8 |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+Multi-Strategy+Whale+Optimization+Algorithm+and+Its+Application&rft.jtitle=Engineering+applications+of+artificial+intelligence&rft.au=Yang%2C+Wenbiao&rft.au=Xia%2C+Kewen&rft.au=Fan%2C+Shurui&rft.au=Wang%2C+Li&rft.date=2022-02-01&rft.pub=Elsevier+Ltd&rft.issn=0952-1976&rft.eissn=1873-6769&rft.volume=108&rft_id=info:doi/10.1016%2Fj.engappai.2021.104558&rft.externalDocID=S0952197621003997 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0952-1976&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0952-1976&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0952-1976&client=summon |