INFO: An efficient optimization algorithm based on weighted mean of vectors
•A novel weighted mean of vectors (INFO) is proposed for global optimization.•The performance of INFO is verified by comparison against other competitive algorithms.•INFO has faster convergence speed and accuracy compared with others.•INFO was validated on 48 functions and four remarkable engineerin...
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Published in | Expert systems with applications Vol. 195; p. 116516 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Elsevier Ltd
01.06.2022
Elsevier BV |
Subjects | |
Online Access | Get full text |
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Abstract | •A novel weighted mean of vectors (INFO) is proposed for global optimization.•The performance of INFO is verified by comparison against other competitive algorithms.•INFO has faster convergence speed and accuracy compared with others.•INFO was validated on 48 functions and four remarkable engineering test cases.•Excellent results have been obtained in engineering experiments.
This study presents the analysis and principle of an innovative optimizer named weIghted meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean method, whereby the weighted mean idea is employed for a solid structure and updating the vectors’ position using three core procedures: updating rule, vector combining, and a local search. The updating rule stage is based on a mean-based law and convergence acceleration to generate new vectors. The vector combining stage creates a combination of obtained vectors with the updating rule to achieve a promising solution. The updating rule and vector combining steps were improved in INFO to increase the exploration and exploitation capacities. Moreover, the local search stage helps this algorithm escape low-accuracy solutions and improve exploitation and convergence. The performance of INFO was evaluated in 48 mathematical test functions, and five constrained engineering test cases including optimal design of 10-reservoir system and 4-reservoir system. According to the literature, the results demonstrate that INFO outperforms other basic and advanced methods in terms of exploration and exploitation. In the case of engineering problems, the results indicate that the INFO can converge to 0.99% of the global optimum solution. Hence, the INFO algorithm is a promising tool for optimal designs in optimization problems, which stems from the considerable efficiency of this algorithm for optimizing constrained cases. The source codes of INFO algorithm are publicly available at https://imanahmadianfar.com. and https://aliasgharheidari.com/INFO.html. |
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AbstractList | •A novel weighted mean of vectors (INFO) is proposed for global optimization.•The performance of INFO is verified by comparison against other competitive algorithms.•INFO has faster convergence speed and accuracy compared with others.•INFO was validated on 48 functions and four remarkable engineering test cases.•Excellent results have been obtained in engineering experiments.
This study presents the analysis and principle of an innovative optimizer named weIghted meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean method, whereby the weighted mean idea is employed for a solid structure and updating the vectors’ position using three core procedures: updating rule, vector combining, and a local search. The updating rule stage is based on a mean-based law and convergence acceleration to generate new vectors. The vector combining stage creates a combination of obtained vectors with the updating rule to achieve a promising solution. The updating rule and vector combining steps were improved in INFO to increase the exploration and exploitation capacities. Moreover, the local search stage helps this algorithm escape low-accuracy solutions and improve exploitation and convergence. The performance of INFO was evaluated in 48 mathematical test functions, and five constrained engineering test cases including optimal design of 10-reservoir system and 4-reservoir system. According to the literature, the results demonstrate that INFO outperforms other basic and advanced methods in terms of exploration and exploitation. In the case of engineering problems, the results indicate that the INFO can converge to 0.99% of the global optimum solution. Hence, the INFO algorithm is a promising tool for optimal designs in optimization problems, which stems from the considerable efficiency of this algorithm for optimizing constrained cases. The source codes of INFO algorithm are publicly available at https://imanahmadianfar.com. and https://aliasgharheidari.com/INFO.html. This study presents the analysis and principle of an innovative optimizer named weIghted meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean method, whereby the weighted mean idea is employed for a solid structure and updating the vectors' position using three core procedures: updating rule, vector combining, and a local search. The updating rule stage is based on a mean-based law and convergence acceleration to generate new vectors. The vector combining stage creates a combination of obtained vectors with the updating rule to achieve a promising solution. The updating rule and vector combining steps were improved in INFO to increase the exploration and exploitation capacities. Moreover, the local search stage helps this algorithm escape low-accuracy solutions and improve exploitation and convergence. The performance of INFO was evaluated in 48 mathematical test functions, and five constrained engineering test cases including optimal design of 10-reservoir system and 4-reservoir system. According to the literature, the results demonstrate that INFO outperforms other basic and advanced methods in terms of exploration and exploitation. In the case of engineering problems, the results indicate that the INFO can converge to 0.99% of the global optimum solution. Hence, the INFO algorithm is a promising tool for optimal designs in optimization problems, which stems from the considerable efficiency of this algorithm for optimizing constrained cases. The source codes of INFO algorithm are publicly available at https://imanahmadianfar.com. and https://aliasgharheidari.com/INFO.html. |
ArticleNumber | 116516 |
Author | Heidari, Ali Asghar Gandomi, Amir H Chen, Huiling Noshadian, Saeed Ahmadianfar, Iman |
Author_xml | – sequence: 1 givenname: Iman surname: Ahmadianfar fullname: Ahmadianfar, Iman email: i.ahmadianfar@bkatu.ac.ir organization: Department of Civil Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran – sequence: 2 givenname: Ali Asghar surname: Heidari fullname: Heidari, Ali Asghar email: as_heidari@ut.ac.ir organization: School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran 1439957131, Iran – sequence: 3 givenname: Saeed surname: Noshadian fullname: Noshadian, Saeed email: Saeed.noshadian@gmail.com organization: Department of Civil Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran – sequence: 4 givenname: Huiling surname: Chen fullname: Chen, Huiling email: chenhuiling.jlu@gmail.com organization: College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, Zhejiang 325035, China – sequence: 5 givenname: Amir H surname: Gandomi fullname: Gandomi, Amir H email: gandomi@uts.edu.au organization: Faculty of Engineering & Information Technology, University of Technology Sydney, NSW 2007, Australia |
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Cites_doi | 10.1016/j.advengsoft.2013.12.007 10.1115/DETC97/DAC-3757 10.1109/JIOT.2020.3033473 10.1016/j.compstruc.2014.03.007 10.1016/j.swevo.2016.01.005 10.1142/S0218213016300015 10.1007/s12652-018-1031-9 10.1016/j.compchemeng.2009.09.006 10.1109/TEVC.2005.857610 10.1016/j.eswa.2021.115079 10.1016/j.advengsoft.2016.01.008 10.1016/j.ins.2005.02.003 10.1109/MCS.2002.1004010 10.1016/j.advwatres.2016.11.001 10.1016/j.ins.2007.06.009 10.1016/j.ins.2020.06.037 10.3934/mbe.2021192 10.1109/TNNLS.2020.2973760 10.1016/j.asoc.2019.04.004 10.1016/j.future.2019.02.028 10.1109/3477.484436 10.1162/EVCO_r_00180 10.1680/wama.900077 10.1029/WR015i005p01017 10.1016/j.amc.2015.06.036 10.1007/s11227-015-1592-8 10.1007/s00366-011-0241-y 10.1016/j.amc.2006.07.105 10.1023/A:1015059928466 10.1080/03081070701303470 10.1109/TCYB.2014.2322602 10.1016/S0045-7825(01)00323-1 10.1007/s11269-017-1753-z 10.1109/TPWRS.2018.2812711 10.1016/j.scitotenv.2019.134244 10.1061/(ASCE)IR.1943-4774.0000963 10.1061/(ASCE)IR.1943-4774.0000832 10.1016/j.swevo.2019.03.004 10.1016/j.eswa.2021.114864 10.1111/itor.12195 10.1007/s00500-019-04577-0 10.1080/01621459.1937.10503522 10.1016/j.knosys.2015.07.006 10.1109/TEVC.2017.2675628 10.1016/j.asoc.2015.01.068 10.1016/j.ins.2008.02.014 10.1007/s10898-007-9149-x 10.1016/j.advengsoft.2015.01.010 10.1016/j.amc.2006.11.033 10.1016/j.asoc.2012.11.026 10.1115/1.1561044 10.1007/s00521-015-1870-7 10.1109/TEC.2017.2669518 10.1126/science.220.4598.671 10.1007/s11269-019-02364-y 10.1016/j.asoc.2017.09.039 10.1007/s11269-018-2122-2 10.1016/j.future.2020.03.055 10.1016/j.comcom.2021.09.027 10.1007/s10462-020-09893-8 10.1007/s11269-016-1358-y 10.1016/j.knosys.2015.12.022 10.1061/(ASCE)WR.1943-5452.0000644 10.1016/j.ins.2009.03.004 10.1016/j.energy.2015.12.096 10.1007/s00500-016-2071-8 10.1007/s11269-019-02393-7 10.1016/j.infsof.2021.106530 10.1016/j.apm.2019.03.046 10.1002/nme.1620210904 10.1061/(ASCE)WR.1943-5452.0000606 10.1016/j.engappai.2006.03.003 10.1016/S0166-3615(99)00046-9 10.1016/j.asoc.2019.105521 10.1287/ijoc.1.3.190 10.1016/j.asoc.2009.08.031 10.1109/4235.585893 10.1007/s00170-011-3496-y 10.1080/01621459.1961.10482090 |
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References | Cao, Gu, Lv, Yang, Zhao, Li (bib533) 2020; 8 Mirjalili (b0360) 2016; 96 Belegundu, Arora (b0085) 1985; 21 Mirjalili, Lewis (b0365) 2016; 95 Geng, Xu, Xiao, Pan (b0190) 2007; 177 Heidari, Mirjalili, Faris, Aljarah, Mafarja, Chen (b0240) 2019; 97 Ahmadianfar, Bozorg-Haddad, Chu (b0035) 2020; 540 Alcala-Fdez, Fernandez, Luengo, Derrac, Garcia, Sanchez, Herrera (b0055) 2011; 17 Dorigo, Maniezzo, Colorni (b0155) 1996; 26 Li, Chen, Wang, Heidari, Mirjalili (b0295) 2020; 111 Demšar (b0140) 2006; 7 Wolpert, Macready (b0495) 1997; 1 Mirjalili (b0355) 2015; 89 Mirjalili, Mirjalili, Lewis (b0375) 2014; 69 Cruz-Chávez, Martínez-Rangel, Cruz-Rosales (b0060) 2017; 24 Ahmadianfar, Samadi-Koucheksaraee, Bozorg-Haddad (b0050) 2017; 31 Bozorg-Haddad, Janbaz, Loáiciga (b0100) 2016; 98 Coello (b0135) 2002; 191 Lai, Leung, Ling (b0285) 2009 Liu, Sun, Xue, Zhang, Yen, Tan (b0320) 2021 Storn, Price (b0460) 1995 Ahmadianfar, Bozorg-Haddad, Chu (b0030) 2019; 33 Gharehchopogh, Gholizadeh (b0195) 2019; 48 . Moeini, Soghrati (b0385) 2020; 24 Bonyadi, Michalewicz (b0095) 2017; 25 Holland (b0245) 1992 Eberhart, R. C., & Kennedy, J. (1995). A new optimizer using particle swarm theory. In Murray, Yakowitz (b0400) 1979; 15 Mahdavi, Fesanghary, Damangir (b0335) 2007; 188 Zaman, Gharehchopogh (b0510) 2021 Ahmadianfar, Kheyrandish, Jamei, Gharabaghi (b0045) 2020 Gandomi, Yang, Alavi (b0180) 2013; 29 Kirkpatrick, Gelatt, Vecchi (b0275) 1983; 220 Zhang, Luo, Wang (b0515) 2008; 178 Nenavath, Jatoth (b0405) 2018; 62 (pp. 51-58). Beyer, Schwefel (b0090) 2002; 1 Ahmadianfar, Khajeh, Asghari-Pari, Chu (b0040) 2019; 80 Ibrahim, Ewees, Oliva, Abd Elaziz, Lu (b0260) 2019; 10 Yuan, Qian (b0505) 2010; 34 Awad, N. H., Ali, M. Z., Suganthan, P. N., Liang, J. J., & Qu, B. Y. (2017). Problem Definitions and Evaluation Criteria for the CEC 2017 Special Session and Competition on Single Objective Real-Parameter Numerical Optimization. Bozorg-Haddad, Afshar, Mariño (b0105) 2011; 164 Mezura-Montes, Coello (b0345) 2008; 37 Liu, Cai, Wang (b0310) 2010; 10 Kumar, Hussain, Singh, Panigrahi (b0280) 2017; 32 Fong, Wang, Xu, Wong, Fiaidhi, Mohammed (b0170) 2016; 72 Siddique, N., & Adeli, H. (2016). Simulated Annealing, Its Variants and Engineering Applications. Coello (b0130) 2000; 41 Ahmadianfar, Adib, Salarijazi (b0020) 2015; 142 Chen, Yin, Fan, Song, Ji, Liu, Zheng (bib534) 2020; 699 Heidari, Ali Abbaspour, Chen (b0230) 2019; 81 Liang, Qin, Suganthan, Baskar (b0305) 2006; 10 Karaboga, Basturk (b0270) 2007; 39 Rashedi, Nezamabadi-Pour, Saryazdi (bib528) 2009; 179 Moravej, Hosseini-Moghari (b0395) 2016; 30 Wu, Zheng, Chen, Zhao, Yu, Mu (bib531) 2021; 133 Ahmadianfar, Heidari, Gandomi, Chu, Chen (bib527) 2021; 181 Passino (b0410) 2002; 22 Luo, Chen, Heidari, Xu, Zhang, Li (b0330) 2019; 73 Haddad, O. B., Afshar, A., & Mariño, M. A. (2011). Multireservoir optimisation in discrete and continuous domains. In Adarsh, Raghunathan, Jayabarathi, Yang (b0015) 2016; 96 Che, Wang (bib530) 2020; 32 Samadi-koucheksaraee, A., Ahmadianfar, I., Bozorg-Haddad, O., & Asghari-pari, S. A. (2018). Gradient Evolution Optimization Algorithm to Optimize Reservoir Operation Systems. Cheng, Jin (b0120) 2015; 45 Talbi (b0470) 2009 Mahi, Baykan, Kodaz (b0340) 2015; 30 Holm (b0250) 1979 Asgari, Bozorg Haddad, Pazoki, Loáiciga (b0070) 2015; 142 Dorigo, M., & Di Caro, G. (1999). Ant colony optimization: a new meta-heuristic. In Chen, Yang, Heidari, Zhao (b0110) 2019; 113018 (Vol. 97, pp. 1997). Dunn (b0160) 1961; 56 Liu, Wu, Wu, Wang (b0315) 2015; 268 Sadollah, Bahreininejad, Eskandar, Hamdi (b0425) 2013; 13 Liang, Liu, Shen, Li, Man (b0300) 2018; 33 Levi (b0290) 2014 Haddad, Moravej, Loáiciga (b0220) 2014; 141 Saka, Hasançebi, Geem (b0430) 2016; 28 Mitchell, M., Holland, J. H., & Forrest, S. (1994). When will a genetic algorithm outperform hill climbing. In (Vol. 1, pp. 39-43): New York, NY. Paterlini, S., & Krink, T. High performance clustering with differential evolution. In (Vol. 2): IEEE. Wu, Zheng, Xia, Lo (bib532) 2021 Mohammadi, Farzin, Mousavi, Karami (b0390) 2019; 33 (Vol. 2, pp. 1470-1477): IEEE. Chow, V. T., & Cortes-Rivera, G. (1974). Application of DDDP in water resources planning. Glover (b0200) 1989; 1 (Vol. 164, pp. 57-72): Thomas Telford Ltd. Goldanloo, Gharehchopogh (b0210) 2021 Sun, Jin, Cheng, Ding, Zeng (b0465) 2017; 21 Jiang, Luo, Wei, Abualigah, Zhou (b0265) 2021; 18 Mirjalili (b0350) 2015; 83 Deng, Zhao, Zou, Li, Yang, Wu (b0145) 2017; 21 Heidari, Aljarah, Faris, Chen, Luo, Mirjalili (b0235) 2019 Cheng, Prayogo (b0115) 2014; 139 Huang, Wang, He (b0255) 2007; 186 Vandenbergh, Engelbrecht (b0480) 2006; 176 Yang, Chen, Heidari, Gandomi (bib526) 2021; 177 Yildiz, Solanki (b0500) 2012; 59 Lin, Song, Ke, Yan, Liu, Cai (bib529) 2022; 181 Tzanetos, Dounias (b0475) 2020; 54 Gold, S., & Krishnamurty, S. (1997). Trade-offs in robust engineering design. In Wang (b0490) 2003; 125 He, Wang (b0225) 2007; 20 Friedman (b0175) 1937; 32 Arora (b0065) 2017 Garousi-Nejad, Bozorg-Haddad, Loáiciga (b0185) 2016; 142 Mirjalili, Mirjalili, Hatamlou (b0370) 2016; 27 Kumar (10.1016/j.eswa.2022.116516_b0280) 2017; 32 Gharehchopogh (10.1016/j.eswa.2022.116516_b0195) 2019; 48 10.1016/j.eswa.2022.116516_b0075 Belegundu (10.1016/j.eswa.2022.116516_b0085) 1985; 21 He (10.1016/j.eswa.2022.116516_b0225) 2007; 20 Haddad (10.1016/j.eswa.2022.116516_b0220) 2014; 141 Vandenbergh (10.1016/j.eswa.2022.116516_b0480) 2006; 176 Yildiz (10.1016/j.eswa.2022.116516_b0500) 2012; 59 Lin (10.1016/j.eswa.2022.116516_bib529) 2022; 181 Zhang (10.1016/j.eswa.2022.116516_b0515) 2008; 178 Cruz-Chávez (10.1016/j.eswa.2022.116516_b0060) 2017; 24 Alcala-Fdez (10.1016/j.eswa.2022.116516_b0055) 2011; 17 Dunn (10.1016/j.eswa.2022.116516_b0160) 1961; 56 Cheng (10.1016/j.eswa.2022.116516_b0115) 2014; 139 Demšar (10.1016/j.eswa.2022.116516_b0140) 2006; 7 Moravej (10.1016/j.eswa.2022.116516_b0395) 2016; 30 Passino (10.1016/j.eswa.2022.116516_b0410) 2002; 22 Gandomi (10.1016/j.eswa.2022.116516_b0180) 2013; 29 Mirjalili (10.1016/j.eswa.2022.116516_b0350) 2015; 83 Moeini (10.1016/j.eswa.2022.116516_b0385) 2020; 24 Mirjalili (10.1016/j.eswa.2022.116516_b0370) 2016; 27 Deng (10.1016/j.eswa.2022.116516_b0145) 2017; 21 Rashedi (10.1016/j.eswa.2022.116516_bib528) 2009; 179 Levi (10.1016/j.eswa.2022.116516_b0290) 2014 Coello (10.1016/j.eswa.2022.116516_b0130) 2000; 41 Saka (10.1016/j.eswa.2022.116516_b0430) 2016; 28 Beyer (10.1016/j.eswa.2022.116516_b0090) 2002; 1 10.1016/j.eswa.2022.116516_b0125 Ahmadianfar (10.1016/j.eswa.2022.116516_bib527) 2021; 181 Coello (10.1016/j.eswa.2022.116516_b0135) 2002; 191 Asgari (10.1016/j.eswa.2022.116516_b0070) 2015; 142 Heidari (10.1016/j.eswa.2022.116516_b0230) 2019; 81 Ahmadianfar (10.1016/j.eswa.2022.116516_b0030) 2019; 33 Mirjalili (10.1016/j.eswa.2022.116516_b0355) 2015; 89 Murray (10.1016/j.eswa.2022.116516_b0400) 1979; 15 Li (10.1016/j.eswa.2022.116516_b0295) 2020; 111 10.1016/j.eswa.2022.116516_b0380 Ibrahim (10.1016/j.eswa.2022.116516_b0260) 2019; 10 Cheng (10.1016/j.eswa.2022.116516_b0120) 2015; 45 Geng (10.1016/j.eswa.2022.116516_b0190) 2007; 177 Liu (10.1016/j.eswa.2022.116516_b0315) 2015; 268 Ahmadianfar (10.1016/j.eswa.2022.116516_b0050) 2017; 31 Talbi (10.1016/j.eswa.2022.116516_b0470) 2009 Bozorg-Haddad (10.1016/j.eswa.2022.116516_b0105) 2011; 164 Dorigo (10.1016/j.eswa.2022.116516_b0155) 1996; 26 Liang (10.1016/j.eswa.2022.116516_b0300) 2018; 33 10.1016/j.eswa.2022.116516_b0415 Goldanloo (10.1016/j.eswa.2022.116516_b0210) 2021 Luo (10.1016/j.eswa.2022.116516_b0330) 2019; 73 10.1016/j.eswa.2022.116516_b0150 Nenavath (10.1016/j.eswa.2022.116516_b0405) 2018; 62 Zaman (10.1016/j.eswa.2022.116516_b0510) 2021 Arora (10.1016/j.eswa.2022.116516_b0065) 2017 Bonyadi (10.1016/j.eswa.2022.116516_b0095) 2017; 25 Fong (10.1016/j.eswa.2022.116516_b0170) 2016; 72 Heidari (10.1016/j.eswa.2022.116516_b0240) 2019; 97 Mezura-Montes (10.1016/j.eswa.2022.116516_b0345) 2008; 37 Wang (10.1016/j.eswa.2022.116516_b0490) 2003; 125 Heidari (10.1016/j.eswa.2022.116516_b0235) 2019 Tzanetos (10.1016/j.eswa.2022.116516_b0475) 2020; 54 Jiang (10.1016/j.eswa.2022.116516_b0265) 2021; 18 Ahmadianfar (10.1016/j.eswa.2022.116516_b0040) 2019; 80 10.1016/j.eswa.2022.116516_b0435 Wolpert (10.1016/j.eswa.2022.116516_b0495) 1997; 1 Holland (10.1016/j.eswa.2022.116516_b0245) 1992 Ahmadianfar (10.1016/j.eswa.2022.116516_b0045) 2020 Mirjalili (10.1016/j.eswa.2022.116516_b0365) 2016; 95 Bozorg-Haddad (10.1016/j.eswa.2022.116516_b0100) 2016; 98 Ahmadianfar (10.1016/j.eswa.2022.116516_b0035) 2020; 540 Liu (10.1016/j.eswa.2022.116516_b0320) 2021 Glover (10.1016/j.eswa.2022.116516_b0200) 1989; 1 Wu (10.1016/j.eswa.2022.116516_bib531) 2021; 133 Yuan (10.1016/j.eswa.2022.116516_b0505) 2010; 34 10.1016/j.eswa.2022.116516_b0445 Storn (10.1016/j.eswa.2022.116516_b0460) 1995 Huang (10.1016/j.eswa.2022.116516_b0255) 2007; 186 Kirkpatrick (10.1016/j.eswa.2022.116516_b0275) 1983; 220 Chen (10.1016/j.eswa.2022.116516_bib534) 2020; 699 Karaboga (10.1016/j.eswa.2022.116516_b0270) 2007; 39 10.1016/j.eswa.2022.116516_b0165 Liu (10.1016/j.eswa.2022.116516_b0310) 2010; 10 Che (10.1016/j.eswa.2022.116516_bib530) 2020; 32 Cao (10.1016/j.eswa.2022.116516_bib533) 2020; 8 Mirjalili (10.1016/j.eswa.2022.116516_b0375) 2014; 69 10.1016/j.eswa.2022.116516_b0205 Yang (10.1016/j.eswa.2022.116516_bib526) 2021; 177 Chen (10.1016/j.eswa.2022.116516_b0110) 2019; 113018 Ahmadianfar (10.1016/j.eswa.2022.116516_b0020) 2015; 142 Mahi (10.1016/j.eswa.2022.116516_b0340) 2015; 30 Wu (10.1016/j.eswa.2022.116516_bib532) 2021 Mohammadi (10.1016/j.eswa.2022.116516_b0390) 2019; 33 10.1016/j.eswa.2022.116516_b0215 Lai (10.1016/j.eswa.2022.116516_b0285) 2009 Sadollah (10.1016/j.eswa.2022.116516_b0425) 2013; 13 Mahdavi (10.1016/j.eswa.2022.116516_b0335) 2007; 188 Mirjalili (10.1016/j.eswa.2022.116516_b0360) 2016; 96 Liang (10.1016/j.eswa.2022.116516_b0305) 2006; 10 Friedman (10.1016/j.eswa.2022.116516_b0175) 1937; 32 Garousi-Nejad (10.1016/j.eswa.2022.116516_b0185) 2016; 142 Sun (10.1016/j.eswa.2022.116516_b0465) 2017; 21 Holm (10.1016/j.eswa.2022.116516_b0250) 1979 Adarsh (10.1016/j.eswa.2022.116516_b0015) 2016; 96 |
References_xml | – volume: 142 start-page: 05015010 year: 2015 ident: b0020 article-title: Optimizing multireservoir operation: Hybrid of bat algorithm and differential evolution publication-title: Journal of Water Resources Planning and Management – volume: 62 start-page: 1019 year: 2018 end-page: 1043 ident: b0405 article-title: Hybridizing sine cosine algorithm with differential evolution for global optimization and object tracking publication-title: Applied Soft Computing – reference: Haddad, O. B., Afshar, A., & Mariño, M. A. (2011). Multireservoir optimisation in discrete and continuous domains. In – reference: Awad, N. H., Ali, M. Z., Suganthan, P. N., Liang, J. J., & Qu, B. Y. (2017). Problem Definitions and Evaluation Criteria for the CEC 2017 Special Session and Competition on Single Objective Real-Parameter Numerical Optimization. – volume: 141 start-page: 04014064 year: 2014 ident: b0220 article-title: Application of the water cycle algorithm to the optimal operation of reservoir systems publication-title: Journal of Irrigation and Drainage Engineering – reference: Eberhart, R. C., & Kennedy, J. (1995). A new optimizer using particle swarm theory. In – volume: 73 start-page: 109 year: 2019 end-page: 123 ident: b0330 article-title: Multi-strategy boosted mutative whale-inspired optimization approaches publication-title: Applied Mathematical Modelling – volume: 45 start-page: 191 year: 2015 end-page: 204 ident: b0120 article-title: A competitive swarm optimizer for large scale optimization publication-title: IEEE Transactions on Cybernetics – volume: 111 start-page: 300 year: 2020 end-page: 323 ident: b0295 article-title: Slime mould algorithm: A new method for stochastic optimization publication-title: Future Generation Computer Systems – volume: 177 start-page: 114864 year: 2021 ident: bib526 article-title: Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts publication-title: Expert Systems with Applications – volume: 13 start-page: 2592 year: 2013 end-page: 2612 ident: b0425 article-title: Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems publication-title: Applied Soft Computing – volume: 139 start-page: 98 year: 2014 end-page: 112 ident: b0115 article-title: Symbiotic organisms search: A new metaheuristic optimization algorithm publication-title: Computers & Structures – volume: 96 start-page: 120 year: 2016 end-page: 133 ident: b0360 article-title: SCA: A sine cosine algorithm for solving optimization problems publication-title: Knowledge-Based Systems – volume: 220 start-page: 671 year: 1983 end-page: 680 ident: b0275 article-title: Optimization by simulated annealing publication-title: Science – reference: Paterlini, S., & Krink, T. High performance clustering with differential evolution. In (Vol. 2): IEEE. – volume: 33 start-page: 4767 year: 2019 end-page: 4782 ident: b0390 article-title: Investigation of a new hybrid optimization algorithm performance in the optimal operation of multi-reservoir benchmark systems publication-title: Water Resources Management – volume: 540 start-page: 131 year: 2020 end-page: 159 ident: b0035 article-title: Gradient-based optimizer: A new Metaheuristic optimization algorithm publication-title: Information Sciences – volume: 8 start-page: 3099 year: 2020 end-page: 3107 ident: bib533 article-title: RFID Reader Anticollision Based on Distributed Parallel Particle Swarm Optimization publication-title: IEEE Internet of Things Journal – volume: 10 start-page: 281 year: 2006 end-page: 295 ident: b0305 article-title: Comprehensive learning particle swarm optimizer for global optimization of multimodal functions publication-title: IEEE Transactions on Evolutionary Computation – volume: 22 start-page: 52 year: 2002 end-page: 67 ident: b0410 article-title: Biomimicry of bacterial foraging for distributed optimization and control publication-title: IEEE Control Systems – volume: 17 start-page: 2 year: 2011 end-page: 3 ident: b0055 article-title: A software tool to assess evolutionary algorithms for data mining problems publication-title: Journal of Multiple-Valued Logic and Soft Computing – reference: (Vol. 2, pp. 1470-1477): IEEE. – volume: 186 start-page: 340 year: 2007 end-page: 356 ident: b0255 article-title: An effective co-evolutionary differential evolution for constrained optimization publication-title: Applied Mathematics and Computation – reference: Gold, S., & Krishnamurty, S. (1997). Trade-offs in robust engineering design. In – volume: 33 start-page: 4265 year: 2019 end-page: 4286 ident: b0030 article-title: Optimizing multiple linear rules for Multi-Reservoir hydropower systems using an optimization method with an adaptation strategy publication-title: Water Resources Management – reference: Mitchell, M., Holland, J. H., & Forrest, S. (1994). When will a genetic algorithm outperform hill climbing. In – volume: 24 start-page: 1119 year: 2017 end-page: 1137 ident: b0060 article-title: Accelerated simulated annealing algorithm applied to the flexible job shop scheduling problem publication-title: International Transactions in Operational Research – volume: 26 start-page: 29 year: 1996 end-page: 41 ident: b0155 article-title: Ant system: Optimization by a colony of cooperating agents publication-title: IEEE Transactions on Systems, Man, and Cybernetics Part B (Cybernetics) – year: 2009 ident: b0470 article-title: Metaheuristics: From design to implementation – reference: Siddique, N., & Adeli, H. (2016). Simulated Annealing, Its Variants and Engineering Applications. – volume: 24 start-page: 10739 year: 2020 end-page: 10754 ident: b0385 article-title: Optimum outflow determination of the multi-reservoir system using constrained improved artificial bee colony algorithm publication-title: Soft Computing – volume: 27 start-page: 495 year: 2016 end-page: 513 ident: b0370 article-title: Multi-Verse Optimizer: A nature-inspired algorithm for global optimization publication-title: Neural Computing and Applications – reference: (pp. 51-58). – volume: 18 start-page: 3813 year: 2021 end-page: 3854 ident: b0265 article-title: An efficient binary Gradient-based optimizer for feature selection publication-title: Mathematical Biosciences And Engineering – volume: 10 start-page: 629 year: 2010 end-page: 640 ident: b0310 article-title: Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization publication-title: Applied Soft Computing – volume: 32 start-page: 36 year: 2020 end-page: 48 ident: bib530 article-title: A two-timescale duplex neurodynamic approach to mixed-integer optimization publication-title: IEEE Transactions on Neural Networks and Learning Systems – year: 2021 ident: bib532 article-title: Data Quality Matters: A Case Study on Data Label Correctness for Security Bug Report Prediction," in publication-title: IEEE Transactions on Software Engineering – volume: 25 start-page: 1 year: 2017 end-page: 54 ident: b0095 article-title: Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review publication-title: Evolutionary Computation – volume: 268 start-page: 246 year: 2015 end-page: 269 ident: b0315 article-title: A novel differential search algorithm and applications for structure design publication-title: Applied Mathematics and Computation – reference: Chow, V. T., & Cortes-Rivera, G. (1974). Application of DDDP in water resources planning. – volume: 142 start-page: 04016029 year: 2016 ident: b0185 article-title: Modified firefly algorithm for solving multireservoir operation in continuous and discrete domains publication-title: Journal of Water Resources Planning and Management – volume: 41 start-page: 113 year: 2000 end-page: 127 ident: b0130 article-title: Use of a self-adaptive penalty approach for engineering optimization problems publication-title: Computers in Industry – volume: 96 start-page: 666 year: 2016 end-page: 675 ident: b0015 article-title: Economic dispatch using chaotic bat algorithm publication-title: Energy – volume: 48 start-page: 1 year: 2019 end-page: 24 ident: b0195 article-title: A comprehensive survey: Whale Optimization Algorithm and its applications publication-title: Swarm and Evolutionary Computation – volume: 699 start-page: 134244 year: 2020 ident: bib534 article-title: Temporal evolution characteristics of PM2. 5 concentration based on continuous wavelet transform publication-title: Science of The Total Environment – volume: 81 start-page: 105521 year: 2019 ident: b0230 article-title: Efficient boosted grey wolf optimizers for global search and kernel extreme learning machine training publication-title: Applied Soft Computing – reference: Samadi-koucheksaraee, A., Ahmadianfar, I., Bozorg-Haddad, O., & Asghari-pari, S. A. (2018). Gradient Evolution Optimization Algorithm to Optimize Reservoir Operation Systems. – volume: 98 start-page: 173 year: 2016 end-page: 185 ident: b0100 article-title: Application of the gravity search algorithm to multi-reservoir operation optimization publication-title: Advances in Water Resources – volume: 33 start-page: 5052 year: 2018 end-page: 5061 ident: b0300 article-title: A hybrid bat algorithm for economic dispatch with random wind power publication-title: IEEE Transactions on Power Systems – volume: 178 start-page: 3043 year: 2008 end-page: 3074 ident: b0515 article-title: Differential evolution with dynamic stochastic selection for constrained optimization publication-title: Information Sciences – volume: 89 start-page: 228 year: 2015 end-page: 249 ident: b0355 article-title: Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm publication-title: Knowledge-Based Systems – volume: 1 start-page: 67 year: 1997 end-page: 82 ident: b0495 article-title: No free lunch theorems for optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 29 start-page: 17 year: 2013 end-page: 35 ident: b0180 article-title: Cuckoo search algorithm: A metaheuristic approach to solve structural optimization problems publication-title: Engineering with Computers – year: 2017 ident: b0065 publication-title: Introduction to optimum design – volume: 164 start-page: 57 year: 2011 end-page: 72 ident: b0105 article-title: Multireservoir optimisation in discrete and continuous domains publication-title: Proceedings of the Institution of Civil Engineers-Water Management – volume: 80 start-page: 888 year: 2019 end-page: 903 ident: b0040 article-title: Developing optimal policies for reservoir systems using a multi-strategy optimization algorithm publication-title: Applied Soft Computing – volume: 125 start-page: 210 year: 2003 end-page: 220 ident: b0490 article-title: Adaptive response surface method using inherited latin hypercube design points publication-title: Journal of Mechanical Design – volume: 142 start-page: 04015055 year: 2015 ident: b0070 article-title: Weed optimization algorithm for optimal reservoir operation publication-title: Journal of Irrigation and Drainage Engineering – volume: 30 start-page: 3389 year: 2016 end-page: 3407 ident: b0395 article-title: Large scale reservoirs system operation optimization: The interior search algorithm (ISA) approach publication-title: Water Resources Management – volume: 32 start-page: 675 year: 1937 end-page: 701 ident: b0175 article-title: The use of ranks to avoid the assumption of normality implicit in the analysis of variance publication-title: Journal of the American Statistical Association – volume: 21 start-page: 644 year: 2017 end-page: 660 ident: b0465 article-title: Surrogate-assisted cooperative swarm optimization of high-dimensional expensive problems publication-title: IEEE Transactions on Evolutionary Computation – year: 1995 ident: b0460 article-title: Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces – year: 2021 ident: b0320 article-title: A Survey on Evolutionary Neural Architecture Search publication-title: IEEE Transactions on Neural Networks And Learning Systems – volume: 20 start-page: 89 year: 2007 end-page: 99 ident: b0225 article-title: An effective co-evolutionary particle swarm optimization for constrained engineering design problems publication-title: Engineering Applications of Artificial Intelligence – volume: 28 start-page: 88 year: 2016 end-page: 97 ident: b0430 article-title: Metaheuristics in structural optimization and discussions on harmony search algorithm publication-title: Swarm and Evolutionary Computation – volume: 97 start-page: 849 year: 2019 end-page: 872 ident: b0240 article-title: Harris hawks optimization: Algorithm and applications publication-title: Future Generation Computer Systems – volume: 10 start-page: 3155 year: 2019 end-page: 3169 ident: b0260 article-title: Improved salp swarm algorithm based on particle swarm optimization for feature selection publication-title: Journal Of Ambient Intelligence And Humanized Computing – volume: 188 start-page: 1567 year: 2007 end-page: 1579 ident: b0335 article-title: An improved harmony search algorithm for solving optimization problems publication-title: Applied Mathematics and Computation – volume: 72 start-page: 3764 year: 2016 end-page: 3786 ident: b0170 article-title: Recent advances in metaheuristic algorithms: Does the Makara dragon exist? publication-title: The Journal of Supercomputing – start-page: 1 year: 2019 end-page: 27 ident: b0235 article-title: An enhanced associative learning-based exploratory whale optimizer for global optimization publication-title: Neural Computing and Applications – volume: 191 start-page: 1245 year: 2002 end-page: 1287 ident: b0135 article-title: Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: A survey of the state of the art publication-title: Computer Methods in Applied Mechanics and Engineering – volume: 37 start-page: 443 year: 2008 end-page: 473 ident: b0345 article-title: An empirical study about the usefulness of evolution strategies to solve constrained optimization problems publication-title: International Journal of General Systems – volume: 113018 year: 2019 ident: b0110 article-title: An efficient double adaptive random spare reinforced whale optimization algorithm publication-title: Expert Systems with Applications – volume: 176 start-page: 937 year: 2006 end-page: 971 ident: b0480 article-title: A study of particle swarm optimization particle trajectories publication-title: Information Sciences – start-page: 1 year: 2021 end-page: 34 ident: b0210 article-title: A hybrid OBL-based firefly algorithm with symbiotic organisms search algorithm for solving continuous optimization problems publication-title: The Journal of Supercomputing – volume: 59 start-page: 367 year: 2012 end-page: 376 ident: b0500 article-title: Multi-objective optimization of vehicle crashworthiness using a new particle swarm based approach publication-title: International Journal of Advanced Manufacturing Technology – volume: 15 start-page: 1017 year: 1979 end-page: 1027 ident: b0400 article-title: Constrained differential dynamic programming and its application to multireservoir control publication-title: Water Resources Research – volume: 95 start-page: 51 year: 2016 end-page: 67 ident: b0365 article-title: The Whale Optimization Algorithm publication-title: Advances in Engineering Software – volume: 34 start-page: 36 year: 2010 end-page: 41 ident: b0505 article-title: A hybrid genetic algorithm for twice continuously differentiable NLP problems publication-title: Computers & Chemical Engineering – reference: (Vol. 164, pp. 57-72): Thomas Telford Ltd. – volume: 21 start-page: 1583 year: 1985 end-page: 1599 ident: b0085 article-title: A study of mathematical programming methods for structural optimization. Part I: Theory publication-title: International Journal for Numerical Methods in Engineering – reference: (Vol. 97, pp. 1997). – volume: 30 start-page: 484 year: 2015 end-page: 490 ident: b0340 article-title: A new hybrid method based on Particle Swarm Optimization, Ant Colony Optimization and 3-Opt algorithms for Traveling Salesman Problem publication-title: Applied Soft Computing – reference: Dorigo, M., & Di Caro, G. (1999). Ant colony optimization: a new meta-heuristic. In – volume: 21 start-page: 4387 year: 2017 end-page: 4398 ident: b0145 article-title: A novel collaborative optimization algorithm in solving complex optimization problems publication-title: Soft Computing – volume: 32 start-page: 983 year: 2017 end-page: 992 ident: b0280 article-title: Single sensor-based MPPT of partially shaded PV system for battery charging by using cauchy and gaussian sine cosine optimization publication-title: IEEE Transactions on Energy Conversion – volume: 1 start-page: 3 year: 2002 end-page: 52 ident: b0090 article-title: Evolution strategies–A comprehensive introduction publication-title: Natural Computing – volume: 133 start-page: 106530 year: 2021 ident: bib531 article-title: Improving high-impact bug report prediction with combination of interactive machine learning and active learning publication-title: Information and Software Technology – year: 2020 ident: b0045 article-title: Optimizing operating rules for multi-reservoir hydropower generation systems: An adaptive hybrid differential evolution algorithm publication-title: Renewable Energy. – volume: 7 start-page: 1 year: 2006 end-page: 30 ident: b0140 article-title: Statistical comparisons of classifiers over multiple data sets publication-title: Journal of Machine Learning Research – start-page: 1 year: 2021 end-page: 35 ident: b0510 article-title: An improved particle swarm optimization with backtracking search optimization algorithm for solving continuous optimization problems publication-title: Engineering with Computers – volume: 181 start-page: 115079 year: 2021 ident: bib527 article-title: RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method publication-title: Expert Systems with Applications – volume: 179 start-page: 2232 year: 2009 end-page: 2248 ident: bib528 article-title: GSA: A gravitational search algorithm publication-title: Information Sciences – year: 1992 ident: b0245 article-title: Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence – volume: 177 start-page: 5064 year: 2007 end-page: 5071 ident: b0190 article-title: A simple simulated annealing algorithm for the maximum clique problem publication-title: Information Sciences – start-page: 65 year: 1979 end-page: 70 ident: b0250 article-title: A simple sequentially rejective multiple test procedure publication-title: Scandinavian journal of statistics – volume: 83 start-page: 80 year: 2015 end-page: 98 ident: b0350 article-title: The Ant Lion Optimizer publication-title: Advances in Engineering Software – start-page: 1116 year: 2009 end-page: 1122 ident: b0285 article-title: A new differential evolution with wavelet theory based mutation operation publication-title: 2009 IEEE Congress on Evolutionary Computation – reference: . – volume: 39 start-page: 459 year: 2007 end-page: 471 ident: b0270 article-title: A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm publication-title: Journal of Global Optimization – volume: 54 start-page: 1841 year: 2020 end-page: 1862 ident: b0475 article-title: Nature inspired optimization algorithms or simply variations of metaheuristics? publication-title: Artificial Intelligence Review – volume: 69 start-page: 46 year: 2014 end-page: 61 ident: b0375 article-title: Grey wolf optimizer publication-title: Advances in Engineering Software – volume: 1 start-page: 190 year: 1989 end-page: 206 ident: b0200 article-title: Tabu search—part I publication-title: ORSA Journal on Computing – volume: 181 start-page: 132 year: 2022 end-page: 142 ident: bib529 article-title: Optimal caching scheme in D2D networks with multiple robot helpers publication-title: Computer Communications – volume: 31 start-page: 4375 year: 2017 end-page: 4397 ident: b0050 article-title: Extracting optimal policies of hydropower multi-reservoir systems utilizing enhanced differential evolution algorithm publication-title: Water Resources Management – volume: 56 start-page: 52 year: 1961 end-page: 64 ident: b0160 article-title: Multiple comparisons among means publication-title: Journal of the American Statistical Association – year: 2014 ident: b0290 article-title: Classical mechanics with calculus of variations and optimal control: an intuitive introduction – reference: (Vol. 1, pp. 39-43): New York, NY. – volume: 69 start-page: 46 year: 2014 ident: 10.1016/j.eswa.2022.116516_b0375 article-title: Grey wolf optimizer publication-title: Advances in Engineering Software doi: 10.1016/j.advengsoft.2013.12.007 – ident: 10.1016/j.eswa.2022.116516_b0205 doi: 10.1115/DETC97/DAC-3757 – volume: 113018 year: 2019 ident: 10.1016/j.eswa.2022.116516_b0110 article-title: An efficient double adaptive random spare reinforced whale optimization algorithm publication-title: Expert Systems with Applications – ident: 10.1016/j.eswa.2022.116516_b0125 – volume: 8 start-page: 3099 issue: 5 year: 2020 ident: 10.1016/j.eswa.2022.116516_bib533 article-title: RFID Reader Anticollision Based on Distributed Parallel Particle Swarm Optimization publication-title: IEEE Internet of Things Journal doi: 10.1109/JIOT.2020.3033473 – volume: 139 start-page: 98 year: 2014 ident: 10.1016/j.eswa.2022.116516_b0115 article-title: Symbiotic organisms search: A new metaheuristic optimization algorithm publication-title: Computers & Structures doi: 10.1016/j.compstruc.2014.03.007 – volume: 28 start-page: 88 year: 2016 ident: 10.1016/j.eswa.2022.116516_b0430 article-title: Metaheuristics in structural optimization and discussions on harmony search algorithm publication-title: Swarm and Evolutionary Computation doi: 10.1016/j.swevo.2016.01.005 – ident: 10.1016/j.eswa.2022.116516_b0445 doi: 10.1142/S0218213016300015 – year: 2014 ident: 10.1016/j.eswa.2022.116516_b0290 – volume: 10 start-page: 3155 issue: 8 year: 2019 ident: 10.1016/j.eswa.2022.116516_b0260 article-title: Improved salp swarm algorithm based on particle swarm optimization for feature selection publication-title: Journal Of Ambient Intelligence And Humanized Computing doi: 10.1007/s12652-018-1031-9 – volume: 34 start-page: 36 issue: 1 year: 2010 ident: 10.1016/j.eswa.2022.116516_b0505 article-title: A hybrid genetic algorithm for twice continuously differentiable NLP problems publication-title: Computers & Chemical Engineering doi: 10.1016/j.compchemeng.2009.09.006 – volume: 10 start-page: 281 issue: 3 year: 2006 ident: 10.1016/j.eswa.2022.116516_b0305 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 – year: 2009 ident: 10.1016/j.eswa.2022.116516_b0470 – volume: 181 start-page: 115079 year: 2021 ident: 10.1016/j.eswa.2022.116516_bib527 article-title: RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2021.115079 – volume: 95 start-page: 51 year: 2016 ident: 10.1016/j.eswa.2022.116516_b0365 article-title: The Whale Optimization Algorithm publication-title: Advances in Engineering Software doi: 10.1016/j.advengsoft.2016.01.008 – start-page: 1 year: 2019 ident: 10.1016/j.eswa.2022.116516_b0235 article-title: An enhanced associative learning-based exploratory whale optimizer for global optimization publication-title: Neural Computing and Applications – start-page: 1 year: 2021 ident: 10.1016/j.eswa.2022.116516_b0210 article-title: A hybrid OBL-based firefly algorithm with symbiotic organisms search algorithm for solving continuous optimization problems publication-title: The Journal of Supercomputing – volume: 176 start-page: 937 issue: 8 year: 2006 ident: 10.1016/j.eswa.2022.116516_b0480 article-title: A study of particle swarm optimization particle trajectories publication-title: Information Sciences doi: 10.1016/j.ins.2005.02.003 – volume: 22 start-page: 52 year: 2002 ident: 10.1016/j.eswa.2022.116516_b0410 article-title: Biomimicry of bacterial foraging for distributed optimization and control publication-title: IEEE Control Systems doi: 10.1109/MCS.2002.1004010 – volume: 98 start-page: 173 year: 2016 ident: 10.1016/j.eswa.2022.116516_b0100 article-title: Application of the gravity search algorithm to multi-reservoir operation optimization publication-title: Advances in Water Resources doi: 10.1016/j.advwatres.2016.11.001 – ident: 10.1016/j.eswa.2022.116516_b0165 – volume: 177 start-page: 5064 issue: 22 year: 2007 ident: 10.1016/j.eswa.2022.116516_b0190 article-title: A simple simulated annealing algorithm for the maximum clique problem publication-title: Information Sciences doi: 10.1016/j.ins.2007.06.009 – volume: 540 start-page: 131 year: 2020 ident: 10.1016/j.eswa.2022.116516_b0035 article-title: Gradient-based optimizer: A new Metaheuristic optimization algorithm publication-title: Information Sciences doi: 10.1016/j.ins.2020.06.037 – volume: 18 start-page: 3813 year: 2021 ident: 10.1016/j.eswa.2022.116516_b0265 article-title: An efficient binary Gradient-based optimizer for feature selection publication-title: Mathematical Biosciences And Engineering doi: 10.3934/mbe.2021192 – volume: 32 start-page: 36 issue: 1 year: 2020 ident: 10.1016/j.eswa.2022.116516_bib530 article-title: A two-timescale duplex neurodynamic approach to mixed-integer optimization publication-title: IEEE Transactions on Neural Networks and Learning Systems doi: 10.1109/TNNLS.2020.2973760 – volume: 80 start-page: 888 year: 2019 ident: 10.1016/j.eswa.2022.116516_b0040 article-title: Developing optimal policies for reservoir systems using a multi-strategy optimization algorithm publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2019.04.004 – volume: 97 start-page: 849 year: 2019 ident: 10.1016/j.eswa.2022.116516_b0240 article-title: Harris hawks optimization: Algorithm and applications publication-title: Future Generation Computer Systems doi: 10.1016/j.future.2019.02.028 – volume: 26 start-page: 29 issue: 1 year: 1996 ident: 10.1016/j.eswa.2022.116516_b0155 article-title: Ant system: Optimization by a colony of cooperating agents publication-title: IEEE Transactions on Systems, Man, and Cybernetics Part B (Cybernetics) doi: 10.1109/3477.484436 – volume: 25 start-page: 1 issue: 1 year: 2017 ident: 10.1016/j.eswa.2022.116516_b0095 article-title: Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review publication-title: Evolutionary Computation doi: 10.1162/EVCO_r_00180 – ident: 10.1016/j.eswa.2022.116516_b0215 doi: 10.1680/wama.900077 – volume: 15 start-page: 1017 issue: 5 year: 1979 ident: 10.1016/j.eswa.2022.116516_b0400 article-title: Constrained differential dynamic programming and its application to multireservoir control publication-title: Water Resources Research doi: 10.1029/WR015i005p01017 – volume: 268 start-page: 246 year: 2015 ident: 10.1016/j.eswa.2022.116516_b0315 article-title: A novel differential search algorithm and applications for structure design publication-title: Applied Mathematics and Computation doi: 10.1016/j.amc.2015.06.036 – volume: 72 start-page: 3764 issue: 10 year: 2016 ident: 10.1016/j.eswa.2022.116516_b0170 article-title: Recent advances in metaheuristic algorithms: Does the Makara dragon exist? publication-title: The Journal of Supercomputing doi: 10.1007/s11227-015-1592-8 – volume: 29 start-page: 17 issue: 1 year: 2013 ident: 10.1016/j.eswa.2022.116516_b0180 article-title: Cuckoo search algorithm: A metaheuristic approach to solve structural optimization problems publication-title: Engineering with Computers doi: 10.1007/s00366-011-0241-y – volume: 186 start-page: 340 issue: 1 year: 2007 ident: 10.1016/j.eswa.2022.116516_b0255 article-title: An effective co-evolutionary differential evolution for constrained optimization publication-title: Applied Mathematics and Computation doi: 10.1016/j.amc.2006.07.105 – volume: 1 start-page: 3 year: 2002 ident: 10.1016/j.eswa.2022.116516_b0090 article-title: Evolution strategies–A comprehensive introduction publication-title: Natural Computing doi: 10.1023/A:1015059928466 – volume: 37 start-page: 443 issue: 4 year: 2008 ident: 10.1016/j.eswa.2022.116516_b0345 article-title: An empirical study about the usefulness of evolution strategies to solve constrained optimization problems publication-title: International Journal of General Systems doi: 10.1080/03081070701303470 – volume: 45 start-page: 191 year: 2015 ident: 10.1016/j.eswa.2022.116516_b0120 article-title: A competitive swarm optimizer for large scale optimization publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TCYB.2014.2322602 – year: 1992 ident: 10.1016/j.eswa.2022.116516_b0245 – volume: 191 start-page: 1245 issue: 11-12 year: 2002 ident: 10.1016/j.eswa.2022.116516_b0135 article-title: Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: A survey of the state of the art publication-title: Computer Methods in Applied Mechanics and Engineering doi: 10.1016/S0045-7825(01)00323-1 – volume: 31 start-page: 4375 issue: 14 year: 2017 ident: 10.1016/j.eswa.2022.116516_b0050 article-title: Extracting optimal policies of hydropower multi-reservoir systems utilizing enhanced differential evolution algorithm publication-title: Water Resources Management doi: 10.1007/s11269-017-1753-z – volume: 33 start-page: 5052 issue: 5 year: 2018 ident: 10.1016/j.eswa.2022.116516_b0300 article-title: A hybrid bat algorithm for economic dispatch with random wind power publication-title: IEEE Transactions on Power Systems doi: 10.1109/TPWRS.2018.2812711 – year: 2017 ident: 10.1016/j.eswa.2022.116516_b0065 – volume: 699 start-page: 134244 year: 2020 ident: 10.1016/j.eswa.2022.116516_bib534 article-title: Temporal evolution characteristics of PM2. 5 concentration based on continuous wavelet transform publication-title: Science of The Total Environment doi: 10.1016/j.scitotenv.2019.134244 – volume: 142 start-page: 04015055 year: 2015 ident: 10.1016/j.eswa.2022.116516_b0070 article-title: Weed optimization algorithm for optimal reservoir operation publication-title: Journal of Irrigation and Drainage Engineering doi: 10.1061/(ASCE)IR.1943-4774.0000963 – volume: 141 start-page: 04014064 year: 2014 ident: 10.1016/j.eswa.2022.116516_b0220 article-title: Application of the water cycle algorithm to the optimal operation of reservoir systems publication-title: Journal of Irrigation and Drainage Engineering doi: 10.1061/(ASCE)IR.1943-4774.0000832 – volume: 48 start-page: 1 year: 2019 ident: 10.1016/j.eswa.2022.116516_b0195 article-title: A comprehensive survey: Whale Optimization Algorithm and its applications publication-title: Swarm and Evolutionary Computation doi: 10.1016/j.swevo.2019.03.004 – volume: 177 start-page: 114864 year: 2021 ident: 10.1016/j.eswa.2022.116516_bib526 article-title: Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2021.114864 – volume: 24 start-page: 1119 issue: 5 year: 2017 ident: 10.1016/j.eswa.2022.116516_b0060 article-title: Accelerated simulated annealing algorithm applied to the flexible job shop scheduling problem publication-title: International Transactions in Operational Research doi: 10.1111/itor.12195 – volume: 24 start-page: 10739 issue: 14 year: 2020 ident: 10.1016/j.eswa.2022.116516_b0385 article-title: Optimum outflow determination of the multi-reservoir system using constrained improved artificial bee colony algorithm publication-title: Soft Computing doi: 10.1007/s00500-019-04577-0 – volume: 164 start-page: 57 issue: 2 year: 2011 ident: 10.1016/j.eswa.2022.116516_b0105 article-title: Multireservoir optimisation in discrete and continuous domains publication-title: Proceedings of the Institution of Civil Engineers-Water Management doi: 10.1680/wama.900077 – volume: 32 start-page: 675 issue: 200 year: 1937 ident: 10.1016/j.eswa.2022.116516_b0175 article-title: The use of ranks to avoid the assumption of normality implicit in the analysis of variance publication-title: Journal of the American Statistical Association doi: 10.1080/01621459.1937.10503522 – volume: 89 start-page: 228 year: 2015 ident: 10.1016/j.eswa.2022.116516_b0355 article-title: Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm publication-title: Knowledge-Based Systems doi: 10.1016/j.knosys.2015.07.006 – volume: 21 start-page: 644 issue: 4 year: 2017 ident: 10.1016/j.eswa.2022.116516_b0465 article-title: Surrogate-assisted cooperative swarm optimization of high-dimensional expensive problems publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2017.2675628 – volume: 30 start-page: 484 year: 2015 ident: 10.1016/j.eswa.2022.116516_b0340 article-title: A new hybrid method based on Particle Swarm Optimization, Ant Colony Optimization and 3-Opt algorithms for Traveling Salesman Problem publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2015.01.068 – volume: 178 start-page: 3043 issue: 15 year: 2008 ident: 10.1016/j.eswa.2022.116516_b0515 article-title: Differential evolution with dynamic stochastic selection for constrained optimization publication-title: Information Sciences doi: 10.1016/j.ins.2008.02.014 – volume: 39 start-page: 459 issue: 3 year: 2007 ident: 10.1016/j.eswa.2022.116516_b0270 article-title: A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm publication-title: Journal of Global Optimization doi: 10.1007/s10898-007-9149-x – volume: 83 start-page: 80 year: 2015 ident: 10.1016/j.eswa.2022.116516_b0350 article-title: The Ant Lion Optimizer publication-title: Advances in Engineering Software doi: 10.1016/j.advengsoft.2015.01.010 – volume: 188 start-page: 1567 issue: 2 year: 2007 ident: 10.1016/j.eswa.2022.116516_b0335 article-title: An improved harmony search algorithm for solving optimization problems publication-title: Applied Mathematics and Computation doi: 10.1016/j.amc.2006.11.033 – volume: 13 start-page: 2592 issue: 5 year: 2013 ident: 10.1016/j.eswa.2022.116516_b0425 article-title: Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2012.11.026 – volume: 17 start-page: 2 year: 2011 ident: 10.1016/j.eswa.2022.116516_b0055 article-title: A software tool to assess evolutionary algorithms for data mining problems publication-title: Journal of Multiple-Valued Logic and Soft Computing – start-page: 1 year: 2021 ident: 10.1016/j.eswa.2022.116516_b0510 article-title: An improved particle swarm optimization with backtracking search optimization algorithm for solving continuous optimization problems publication-title: Engineering with Computers – volume: 125 start-page: 210 year: 2003 ident: 10.1016/j.eswa.2022.116516_b0490 article-title: Adaptive response surface method using inherited latin hypercube design points publication-title: Journal of Mechanical Design doi: 10.1115/1.1561044 – volume: 27 start-page: 495 issue: 2 year: 2016 ident: 10.1016/j.eswa.2022.116516_b0370 article-title: Multi-Verse Optimizer: A nature-inspired algorithm for global optimization publication-title: Neural Computing and Applications doi: 10.1007/s00521-015-1870-7 – volume: 7 start-page: 1 year: 2006 ident: 10.1016/j.eswa.2022.116516_b0140 article-title: Statistical comparisons of classifiers over multiple data sets publication-title: Journal of Machine Learning Research – volume: 32 start-page: 983 issue: 3 year: 2017 ident: 10.1016/j.eswa.2022.116516_b0280 article-title: Single sensor-based MPPT of partially shaded PV system for battery charging by using cauchy and gaussian sine cosine optimization publication-title: IEEE Transactions on Energy Conversion doi: 10.1109/TEC.2017.2669518 – volume: 220 start-page: 671 issue: 4598 year: 1983 ident: 10.1016/j.eswa.2022.116516_b0275 article-title: Optimization by simulated annealing publication-title: Science doi: 10.1126/science.220.4598.671 – volume: 33 start-page: 4265 issue: 12 year: 2019 ident: 10.1016/j.eswa.2022.116516_b0030 article-title: Optimizing multiple linear rules for Multi-Reservoir hydropower systems using an optimization method with an adaptation strategy publication-title: Water Resources Management doi: 10.1007/s11269-019-02364-y – ident: 10.1016/j.eswa.2022.116516_b0150 – year: 2021 ident: 10.1016/j.eswa.2022.116516_b0320 article-title: A Survey on Evolutionary Neural Architecture Search publication-title: IEEE Transactions on Neural Networks And Learning Systems – volume: 62 start-page: 1019 year: 2018 ident: 10.1016/j.eswa.2022.116516_b0405 article-title: Hybridizing sine cosine algorithm with differential evolution for global optimization and object tracking publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2017.09.039 – ident: 10.1016/j.eswa.2022.116516_b0435 doi: 10.1007/s11269-018-2122-2 – volume: 111 start-page: 300 year: 2020 ident: 10.1016/j.eswa.2022.116516_b0295 article-title: Slime mould algorithm: A new method for stochastic optimization publication-title: Future Generation Computer Systems doi: 10.1016/j.future.2020.03.055 – volume: 181 start-page: 132 year: 2022 ident: 10.1016/j.eswa.2022.116516_bib529 article-title: Optimal caching scheme in D2D networks with multiple robot helpers publication-title: Computer Communications doi: 10.1016/j.comcom.2021.09.027 – volume: 54 start-page: 1841 issue: 3 year: 2020 ident: 10.1016/j.eswa.2022.116516_b0475 article-title: Nature inspired optimization algorithms or simply variations of metaheuristics? publication-title: Artificial Intelligence Review doi: 10.1007/s10462-020-09893-8 – volume: 30 start-page: 3389 issue: 10 year: 2016 ident: 10.1016/j.eswa.2022.116516_b0395 article-title: Large scale reservoirs system operation optimization: The interior search algorithm (ISA) approach publication-title: Water Resources Management doi: 10.1007/s11269-016-1358-y – volume: 96 start-page: 120 year: 2016 ident: 10.1016/j.eswa.2022.116516_b0360 article-title: SCA: A sine cosine algorithm for solving optimization problems publication-title: Knowledge-Based Systems doi: 10.1016/j.knosys.2015.12.022 – volume: 142 start-page: 04016029 issue: 9 year: 2016 ident: 10.1016/j.eswa.2022.116516_b0185 article-title: Modified firefly algorithm for solving multireservoir operation in continuous and discrete domains publication-title: Journal of Water Resources Planning and Management doi: 10.1061/(ASCE)WR.1943-5452.0000644 – ident: 10.1016/j.eswa.2022.116516_b0380 – volume: 179 start-page: 2232 issue: 13 year: 2009 ident: 10.1016/j.eswa.2022.116516_bib528 article-title: GSA: A gravitational search algorithm publication-title: Information Sciences doi: 10.1016/j.ins.2009.03.004 – volume: 96 start-page: 666 year: 2016 ident: 10.1016/j.eswa.2022.116516_b0015 article-title: Economic dispatch using chaotic bat algorithm publication-title: Energy doi: 10.1016/j.energy.2015.12.096 – volume: 21 start-page: 4387 issue: 15 year: 2017 ident: 10.1016/j.eswa.2022.116516_b0145 article-title: A novel collaborative optimization algorithm in solving complex optimization problems publication-title: Soft Computing doi: 10.1007/s00500-016-2071-8 – year: 2021 ident: 10.1016/j.eswa.2022.116516_bib532 article-title: Data Quality Matters: A Case Study on Data Label Correctness for Security Bug Report Prediction," in publication-title: IEEE Transactions on Software Engineering – volume: 33 start-page: 4767 issue: 14 year: 2019 ident: 10.1016/j.eswa.2022.116516_b0390 article-title: Investigation of a new hybrid optimization algorithm performance in the optimal operation of multi-reservoir benchmark systems publication-title: Water Resources Management doi: 10.1007/s11269-019-02393-7 – volume: 133 start-page: 106530 year: 2021 ident: 10.1016/j.eswa.2022.116516_bib531 article-title: Improving high-impact bug report prediction with combination of interactive machine learning and active learning publication-title: Information and Software Technology doi: 10.1016/j.infsof.2021.106530 – start-page: 1116 year: 2009 ident: 10.1016/j.eswa.2022.116516_b0285 article-title: A new differential evolution with wavelet theory based mutation operation – volume: 73 start-page: 109 year: 2019 ident: 10.1016/j.eswa.2022.116516_b0330 article-title: Multi-strategy boosted mutative whale-inspired optimization approaches publication-title: Applied Mathematical Modelling doi: 10.1016/j.apm.2019.03.046 – volume: 21 start-page: 1583 year: 1985 ident: 10.1016/j.eswa.2022.116516_b0085 article-title: A study of mathematical programming methods for structural optimization. Part I: Theory publication-title: International Journal for Numerical Methods in Engineering doi: 10.1002/nme.1620210904 – volume: 142 start-page: 05015010 year: 2015 ident: 10.1016/j.eswa.2022.116516_b0020 article-title: Optimizing multireservoir operation: Hybrid of bat algorithm and differential evolution publication-title: Journal of Water Resources Planning and Management doi: 10.1061/(ASCE)WR.1943-5452.0000606 – year: 2020 ident: 10.1016/j.eswa.2022.116516_b0045 article-title: Optimizing operating rules for multi-reservoir hydropower generation systems: An adaptive hybrid differential evolution algorithm publication-title: Renewable Energy. – year: 1995 ident: 10.1016/j.eswa.2022.116516_b0460 – volume: 20 start-page: 89 issue: 1 year: 2007 ident: 10.1016/j.eswa.2022.116516_b0225 article-title: An effective co-evolutionary particle swarm optimization for constrained engineering design problems publication-title: Engineering Applications of Artificial Intelligence doi: 10.1016/j.engappai.2006.03.003 – volume: 41 start-page: 113 issue: 2 year: 2000 ident: 10.1016/j.eswa.2022.116516_b0130 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 – start-page: 65 year: 1979 ident: 10.1016/j.eswa.2022.116516_b0250 article-title: A simple sequentially rejective multiple test procedure publication-title: Scandinavian journal of statistics – volume: 81 start-page: 105521 year: 2019 ident: 10.1016/j.eswa.2022.116516_b0230 article-title: Efficient boosted grey wolf optimizers for global search and kernel extreme learning machine training publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2019.105521 – volume: 1 start-page: 190 issue: 3 year: 1989 ident: 10.1016/j.eswa.2022.116516_b0200 article-title: Tabu search—part I publication-title: ORSA Journal on Computing doi: 10.1287/ijoc.1.3.190 – ident: 10.1016/j.eswa.2022.116516_b0415 – volume: 10 start-page: 629 issue: 2 year: 2010 ident: 10.1016/j.eswa.2022.116516_b0310 article-title: Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2009.08.031 – volume: 1 start-page: 67 issue: 1 year: 1997 ident: 10.1016/j.eswa.2022.116516_b0495 article-title: No free lunch theorems for optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.585893 – ident: 10.1016/j.eswa.2022.116516_b0075 – volume: 59 start-page: 367 issue: 1-4 year: 2012 ident: 10.1016/j.eswa.2022.116516_b0500 article-title: Multi-objective optimization of vehicle crashworthiness using a new particle swarm based approach publication-title: International Journal of Advanced Manufacturing Technology doi: 10.1007/s00170-011-3496-y – volume: 56 start-page: 52 issue: 293 year: 1961 ident: 10.1016/j.eswa.2022.116516_b0160 article-title: Multiple comparisons among means publication-title: Journal of the American Statistical Association doi: 10.1080/01621459.1961.10482090 |
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Snippet | •A novel weighted mean of vectors (INFO) is proposed for global optimization.•The performance of INFO is verified by comparison against other competitive... This study presents the analysis and principle of an innovative optimizer named weIghted meaN oF vectOrs (INFO) to optimize different problems. INFO is a... |
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SubjectTerms | Algorithm Algorithms Artificial intelligence Benchmark Convergence Exploitation Functions (mathematics) Genetic algorithm Global optimization INFO INFO optimization algorithm Mathematical analysis Metaheuristic Optimization Reservoirs Swarm intelligence Vectors (mathematics) Weighted mean of vectors |
Title | INFO: An efficient optimization algorithm based on weighted mean of vectors |
URI | https://dx.doi.org/10.1016/j.eswa.2022.116516 https://www.proquest.com/docview/2647397451 |
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