Alpine skiing optimization: A new bio-inspired optimization algorithm
•A mathematical model is proposed to simulate the behaviors of skiers competing for the championship.•A novel optimization algorithm is proposed using the mathematical model.•The proposed alpine skiing optimization (ASO) algorithm is tested on twenty-three unconstrained benchmark functions and four...
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| Vydáno v: | Advances in engineering software (1992) Ročník 170; s. 103158 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier Ltd
01.08.2022
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| Témata: | |
| ISSN: | 0965-9978 |
| On-line přístup: | Získat plný text |
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| Abstract | •A mathematical model is proposed to simulate the behaviors of skiers competing for the championship.•A novel optimization algorithm is proposed using the mathematical model.•The proposed alpine skiing optimization (ASO) algorithm is tested on twenty-three unconstrained benchmark functions and four engineering design problems.•The results indicate that ASO can be used as a state-of-the-art optimization algorithm to solve engineering optimization problems.•ASO is applied to ensure the parameter of an auto drum fashioned brake. The braking efficiency factor can be improved 28.446% compared with the initial design. Results reveal that ASO is appreciated for complex engineering optimization problem due to its high efficiency, strong reliability and robust exploration performances.
A novel swarm intelligence optimization algorithm is proposed, which is named alpine skiing optimization (ASO). The main inspiration of the ASO originated from the behaviors of skiers competing for the championship. In the ASO, physical stamina and sprint are two essential factors for skiers to win the tournament, which are similar to the two stages of exploration and exploitation. The skiers revealed the behaviour of winning the tournament according to the static sliding and dynamic sliding. This work simulates this behaviour from a mathematical perspective and develops the ASO algorithm. The performance of the ASO algorithm is investigated, through a comparison with many competitive optimization algorithms and four constrained engineering problems. The statistical results validate that the ASO can provide competitive results compared to other state-of-the-art optimization algorithms. Furthermore, ASO is applied to optimize the parameter of an auto drum fashioned brake engineering problem. The objective function is chosen to maximize the braking efficiency coefficient. Results show that the braking efficiency factor is improved by 28.446% compared with the initial design. |
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| AbstractList | •A mathematical model is proposed to simulate the behaviors of skiers competing for the championship.•A novel optimization algorithm is proposed using the mathematical model.•The proposed alpine skiing optimization (ASO) algorithm is tested on twenty-three unconstrained benchmark functions and four engineering design problems.•The results indicate that ASO can be used as a state-of-the-art optimization algorithm to solve engineering optimization problems.•ASO is applied to ensure the parameter of an auto drum fashioned brake. The braking efficiency factor can be improved 28.446% compared with the initial design. Results reveal that ASO is appreciated for complex engineering optimization problem due to its high efficiency, strong reliability and robust exploration performances.
A novel swarm intelligence optimization algorithm is proposed, which is named alpine skiing optimization (ASO). The main inspiration of the ASO originated from the behaviors of skiers competing for the championship. In the ASO, physical stamina and sprint are two essential factors for skiers to win the tournament, which are similar to the two stages of exploration and exploitation. The skiers revealed the behaviour of winning the tournament according to the static sliding and dynamic sliding. This work simulates this behaviour from a mathematical perspective and develops the ASO algorithm. The performance of the ASO algorithm is investigated, through a comparison with many competitive optimization algorithms and four constrained engineering problems. The statistical results validate that the ASO can provide competitive results compared to other state-of-the-art optimization algorithms. Furthermore, ASO is applied to optimize the parameter of an auto drum fashioned brake engineering problem. The objective function is chosen to maximize the braking efficiency coefficient. Results show that the braking efficiency factor is improved by 28.446% compared with the initial design. |
| ArticleNumber | 103158 |
| Author | Wang, Shuo Wang, Zhenxi Ren, Jianji Yuan, Yongliang Zhao, Wu Mu, Xiaokai |
| Author_xml | – sequence: 1 givenname: Yongliang surname: Yuan fullname: Yuan, Yongliang organization: School of Mechanical and Power Engineering, Henan Polytechnic University, Jiaozuo 454003, China – sequence: 2 givenname: Jianji surname: Ren fullname: Ren, Jianji email: renjianji@hpu.edu.cn organization: School of Software, Henan Polytechnic University, Jiaozuo 454003, China – sequence: 3 givenname: Shuo surname: Wang fullname: Wang, Shuo organization: School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China – sequence: 4 givenname: Zhenxi surname: Wang fullname: Wang, Zhenxi organization: School of Software, Henan Polytechnic University, Jiaozuo 454003, China – sequence: 5 givenname: Xiaokai surname: Mu fullname: Mu, Xiaokai organization: School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China – sequence: 6 givenname: Wu surname: Zhao fullname: Zhao, Wu organization: School of Mechanical and Power Engineering, Henan Polytechnic University, Jiaozuo 454003, China |
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| Cites_doi | 10.1016/j.apm.2015.10.040 10.1016/j.ins.2015.06.044 10.1016/j.ijepes.2016.01.037 10.1016/j.advengsoft.2015.01.010 10.1016/j.advengsoft.2017.01.004 10.1016/j.mechmachtheory.2006.02.004 10.1016/j.cnsns.2013.08.027 10.1007/s00366-011-0241-y 10.1016/j.cma.2021.114194 10.3901/JME.2021.06.211 10.1016/j.asoc.2009.08.031 10.1063/5.0035635 10.1109/3477.484436 10.1007/s00158-009-0454-5 10.1016/j.procs.2019.11.284 10.1016/j.ins.2009.03.004 10.1016/j.future.2020.03.055 10.1080/0305215X.2019.1618290 10.1016/j.future.2019.02.028 10.1007/s00158-008-0238-3 10.1016/j.eswa.2012.12.045 10.1016/j.knosys.2015.12.020 10.1038/scientificamerican0792-66 10.2991/ijcis.d.210309.001 10.1016/j.cad.2010.12.015 10.2528/PIER07082403 10.1080/03052150108940941 10.1016/j.knosys.2015.07.006 10.1109/4235.585893 10.1108/EC-08-2019-0362 10.1016/j.asoc.2021.107574 10.1016/j.compstruc.2012.07.010 10.1016/j.ins.2011.08.006 10.1109/TEVC.2008.927706 10.1162/106365603321828970 10.1080/03052150500066737 10.1016/j.physrep.2016.08.001 10.1007/s10898-007-9149-x 10.4018/IJSIR.2016070102 10.1109/ACCESS.2019.2923468 10.1023/A:1008202821328 10.1016/j.mechmachtheory.2006.10.002 10.1016/j.gaitpost.2017.10.007 10.1016/j.swevo.2013.12.005 10.1016/j.engappai.2017.07.005 |
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| Keywords | Alpine skiing optimization algorithm Physical stamina Swarm intelligence Auto drum fashioned brake Constrained optimization |
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| References | Gandomi, Yang, Alavi (bib0047) 2013; 29 Seyedali (bib0044) 2016; 27 de Melo, Carosio (bib0059) 2013; 40 Gandomi, Yang, Alavi (bib0010) 2013; 29 Askarzadeh (bib0030) 2014; 19 Storn, Price (bib0009) 1997; 11 Rao, Savsani, Vakharia (bib0053) 2011; 43 Precup, Hedrea, Roman, Petriu, Szedlak-Stinean, Bojan-Dragos (bib0017) 2020; 99 Precup, David, Roman, Petriu, Szedlak-Stinean (bib0020) 2021; 14 Yu, Wang, Wang (bib0033) 2016; 96 More, Lalit, Nidul (bib0038) 2016; 80 Nikolaus, Sibylle, Petros (bib0043) 2003; 11 Heidari, Mirjalili, Faris, Aljarah, Mafarja, Chen (bib0003) 2019; 97 Qin, Huang, Suganthan (bib0042) 2009; 13 Yuan, Wang, Lv, Song (bib0002) 2021; 38 Formato (bib0013) 2007; 77 Rashedi, Nezamabadi-Pour, Saryazdi (bib0011) 2009; 179 Hein, Hentschel, Runkler, Udluft (bib0018) 2016; 7 Eskandar, Sadollah, Bahreininejad, Hamdi (bib0052) 2012; 110 Eberhart, Kennedy (bib0008) 1995 Rao, Savsani, Vakharia (bib0014) 2012; 183 Liu, Cai, Wang (bib0057) 2010; 10 Liu, Cai, Wang (bib0050) 2010; 10 Premku, Pradeep, Sowmya (bib0026) 2021 Karaboga, Basturk (bib0007) 2007; 39 Zapata, Perozo, Angulo, Contreras (bib0016) 2020; 18 Li, Chen, Wang (bib0024) 2020 Dehkordi, Sadiq, Mirjalili (bib0029) 2021; 109 Ray, Saini (bib0049) 2001; 33 Akira, Aya, Ryosuke, Kohei, Hiroshi (bib0034) 2018; 59 Yang (bib0035) 2010 Zhao, Wang, Mirjalili (bib0051) 2022; 388 Yuan, Mu, Shao (bib0025) 2022 Saremi, Mirjalili, Lewis (bib0046) 2017; 105 Savsani, Savsani (bib0054) 2016; 40 Hein, Hentschel, Runkler, Udluft (bib0015) 2017; 65 Yuan, Guo, Wang, Song (bib0005) 2021; 57 Seyedali (bib0041) 2015; 89 Song, Li (bib0045) 2017 Wang, Yuan, Guo (bib0022) 2019; 7 Wang, Li (bib0058) 2010; 41 Holland (bib0006) 1992; 267 Rao, Tiwari (bib0055) 2007; 42 Gupta, Tiwari, Nair (bib0060) 2007; 42 Tsai (bib0048) 2005; 37 Ahmed, Sheikh, Mirjalili (bib0027) 2022 Wang, Cai, Zhou, Fan (bib0056) 2009; 37 Seyedali (bib0040) 2015; 83 Roman, Precup, Dragos, Szedlak-Stinean (bib0019) 2019; 162 Zhao, Wang, Mirjalili (bib0028) 2022 Aljarah, Faris, Mirjalili (bib0037) 2016; 47 Wolpert, Macready (bib0032) 1997; 1 Li, Zhou, Zhang, Song (bib0036) 2016; 8 Zhao, Zhang, Wang (bib0061) 2020; 87 Salcedo-Sanz (bib0031) 2016; 655 Yuan, Lv, Wang, Song (bib0001) 2020; 52 Vivek, Vimal (bib0004) 2015; 324 Yuan, Ren, Zu, Mu (bib0021) 2021; 11 Dorigo, Maniezzo, Colorni (bib0012) 1996; 26 Satapathy, Naik (bib0039) 2014; 16 Faramarzi, Heidarinejad, Stephens (bib0023) 2020 Seyedali (10.1016/j.advengsoft.2022.103158_bib0044) 2016; 27 Savsani (10.1016/j.advengsoft.2022.103158_bib0054) 2016; 40 Yuan (10.1016/j.advengsoft.2022.103158_bib0021) 2021; 11 Zhao (10.1016/j.advengsoft.2022.103158_bib0051) 2022; 388 Zhao (10.1016/j.advengsoft.2022.103158_bib0061) 2020; 87 Rao (10.1016/j.advengsoft.2022.103158_bib0053) 2011; 43 Eskandar (10.1016/j.advengsoft.2022.103158_bib0052) 2012; 110 Wang (10.1016/j.advengsoft.2022.103158_bib0058) 2010; 41 Song (10.1016/j.advengsoft.2022.103158_bib0045) 2017 Li (10.1016/j.advengsoft.2022.103158_bib0024) 2020 Zapata (10.1016/j.advengsoft.2022.103158_bib0016) 2020; 18 Precup (10.1016/j.advengsoft.2022.103158_bib0020) 2021; 14 Yuan (10.1016/j.advengsoft.2022.103158_bib0005) 2021; 57 Dorigo (10.1016/j.advengsoft.2022.103158_bib0012) 1996; 26 Heidari (10.1016/j.advengsoft.2022.103158_bib0003) 2019; 97 Nikolaus (10.1016/j.advengsoft.2022.103158_bib0043) 2003; 11 Yang (10.1016/j.advengsoft.2022.103158_bib0035) 2010 Dehkordi (10.1016/j.advengsoft.2022.103158_bib0029) 2021; 109 Qin (10.1016/j.advengsoft.2022.103158_bib0042) 2009; 13 Gandomi (10.1016/j.advengsoft.2022.103158_bib0047) 2013; 29 Wang (10.1016/j.advengsoft.2022.103158_bib0056) 2009; 37 Precup (10.1016/j.advengsoft.2022.103158_bib0017) 2020; 99 Yuan (10.1016/j.advengsoft.2022.103158_bib0002) 2021; 38 Ahmed (10.1016/j.advengsoft.2022.103158_bib0027) 2022 Li (10.1016/j.advengsoft.2022.103158_bib0036) 2016; 8 Wang (10.1016/j.advengsoft.2022.103158_bib0022) 2019; 7 Wolpert (10.1016/j.advengsoft.2022.103158_bib0032) 1997; 1 Yu (10.1016/j.advengsoft.2022.103158_bib0033) 2016; 96 Salcedo-Sanz (10.1016/j.advengsoft.2022.103158_bib0031) 2016; 655 Karaboga (10.1016/j.advengsoft.2022.103158_bib0007) 2007; 39 Vivek (10.1016/j.advengsoft.2022.103158_bib0004) 2015; 324 Seyedali (10.1016/j.advengsoft.2022.103158_bib0041) 2015; 89 Eberhart (10.1016/j.advengsoft.2022.103158_bib0008) 1995 Yuan (10.1016/j.advengsoft.2022.103158_bib0025) 2022 Hein (10.1016/j.advengsoft.2022.103158_bib0018) 2016; 7 Ray (10.1016/j.advengsoft.2022.103158_bib0049) 2001; 33 Storn (10.1016/j.advengsoft.2022.103158_bib0009) 1997; 11 Askarzadeh (10.1016/j.advengsoft.2022.103158_bib0030) 2014; 19 Satapathy (10.1016/j.advengsoft.2022.103158_bib0039) 2014; 16 Saremi (10.1016/j.advengsoft.2022.103158_bib0046) 2017; 105 Rao (10.1016/j.advengsoft.2022.103158_bib0014) 2012; 183 Formato (10.1016/j.advengsoft.2022.103158_bib0013) 2007; 77 More (10.1016/j.advengsoft.2022.103158_bib0038) 2016; 80 Roman (10.1016/j.advengsoft.2022.103158_bib0019) 2019; 162 Liu (10.1016/j.advengsoft.2022.103158_bib0057) 2010; 10 Gandomi (10.1016/j.advengsoft.2022.103158_bib0010) 2013; 29 Akira (10.1016/j.advengsoft.2022.103158_bib0034) 2018; 59 Aljarah (10.1016/j.advengsoft.2022.103158_bib0037) 2016; 47 Gupta (10.1016/j.advengsoft.2022.103158_bib0060) 2007; 42 Yuan (10.1016/j.advengsoft.2022.103158_bib0001) 2020; 52 Liu (10.1016/j.advengsoft.2022.103158_bib0050) 2010; 10 Premku (10.1016/j.advengsoft.2022.103158_bib0026) 2021 de Melo (10.1016/j.advengsoft.2022.103158_bib0059) 2013; 40 Hein (10.1016/j.advengsoft.2022.103158_bib0015) 2017; 65 Faramarzi (10.1016/j.advengsoft.2022.103158_bib0023) 2020 Rao (10.1016/j.advengsoft.2022.103158_bib0055) 2007; 42 Zhao (10.1016/j.advengsoft.2022.103158_bib0028) 2022 Seyedali (10.1016/j.advengsoft.2022.103158_bib0040) 2015; 83 Tsai (10.1016/j.advengsoft.2022.103158_bib0048) 2005; 37 Holland (10.1016/j.advengsoft.2022.103158_bib0006) 1992; 267 Rashedi (10.1016/j.advengsoft.2022.103158_bib0011) 2009; 179 |
| References_xml | – volume: 52 start-page: 915 year: 2020 end-page: 931 ident: bib0001 article-title: Optimization of a frame structure using the Coulomb force search strategy-based dragonfly algorithm publication-title: Eng Optim – volume: 11 start-page: 25012 year: 2021 ident: bib0021 article-title: An adaptive instinctive reaction strategy based on Harris hawks optimization algorithm for numerical optimization problems publication-title: AIP Adv – volume: 96 start-page: 156 year: 2016 end-page: 170 ident: bib0033 article-title: Multiple learning particle swarm optimization with space transformation perturbation and its application in ethylene cracking furnace optimization publication-title: Knowl Based Syst – volume: 105 start-page: 30 year: 2017 end-page: 47 ident: bib0046 article-title: Grasshopper optimisation algorithm: theory and application publication-title: Adv Eng Softw – volume: 16 start-page: 28 year: 2014 end-page: 37 ident: bib0039 article-title: Modified teaching-learning-based optimization algorithm for global numerical optimization-a comparative study publication-title: Swarm Evol Comput – volume: 89 start-page: 228 year: 2015 end-page: 249 ident: bib0041 article-title: Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm publication-title: Knowl Based Syst – volume: 42 start-page: 1418 year: 2007 end-page: 1443 ident: bib0060 article-title: Multi-objective design optimisation of rolling bearings using genetic algorithms publication-title: Mech Mach Theory – volume: 33 start-page: 735 year: 2001 end-page: 748 ident: bib0049 article-title: Engineering design optimization using a swarm with an intelligent information sharing among individuals publication-title: Eng Optim – volume: 80 start-page: 52 year: 2016 end-page: 63 ident: bib0038 article-title: Automatic generation control of a multi-area system using ant lion optimizer algorithm based PID plus second order derivative controller publication-title: Int J Electr Power Energy Syst – volume: 43 start-page: 303 year: 2011 end-page: 315 ident: bib0053 article-title: Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems publication-title: Comput Aided Des – volume: 97 start-page: 849 year: 2019 end-page: 872 ident: bib0003 article-title: Harris hawks optimization: algorithm and applications publication-title: Future Gener Comput Syst – volume: 18 start-page: 1 year: 2020 end-page: 18 ident: bib0016 article-title: A hybrid swarm algorithm for collective construction of 3d structures publication-title: Int J Artif Intell – volume: 40 start-page: 3370 year: 2013 end-page: 3377 ident: bib0059 article-title: Investigating multi-view differential evolution for solving constrained engineering design problems publication-title: Expert Syst Appl – volume: 19 start-page: 1213 year: 2014 end-page: 1228 ident: bib0030 article-title: Bird mating optimizer: an optimization algorithm inspired by bird mating strategies publication-title: Commun Nonlinear Sci Numer Simul – volume: 1 start-page: 67 year: 1997 end-page: 82 ident: bib0032 article-title: No free lunch theorems for optimization publication-title: IEEE Trans Evol Comput – year: 2020 ident: bib0023 article-title: Equilibrium optimizer: a novel optimization algorithm publication-title: Knowl Based Syst – volume: 10 start-page: 629 year: 2010 end-page: 640 ident: bib0057 article-title: Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization publication-title: Appl Soft Comput – volume: 324 start-page: 217 year: 2015 end-page: 246 ident: bib0004 article-title: Heat transfer search (HTS): a novel optimization algorithm publication-title: Inform Sci – volume: 7 start-page: 80570 year: 2019 end-page: 80576 ident: bib0022 article-title: An improved rider optimization algorithm for solving engineering optimization problems publication-title: IEEE Access – volume: 65 start-page: 87 year: 2017 end-page: 98 ident: bib0015 article-title: Particle swarm optimization for generating interpretable fuzzy reinforcement learning policies publication-title: Eng Appl Artif Intell – volume: 162 start-page: 267 year: 2019 end-page: 274 ident: bib0019 article-title: Combined Model-free adaptive control with fuzzy component by virtual reference feedback tuning for tower crane systems publication-title: Proced Comput Sci – start-page: 300 year: 2020 end-page: 323 ident: bib0024 article-title: Slime mould algorithm: a new method for stochastic optimization publication-title: Future Gener Comp Syst – volume: 7 start-page: 23 year: 2016 end-page: 42 ident: bib0018 article-title: Reinforcement learning with particle swarm optimization policy (pso-p) in continuous state and action spaces publication-title: Int J Swarm Intell Res – start-page: 1178 year: 2017 end-page: 1183 ident: bib0045 article-title: Elite opposition learning and exponential function steps-based dragonfly algorithm for global optimization – volume: 26 start-page: 29 year: 1996 end-page: 41 ident: bib0012 article-title: Ant system: optimization by a colony of cooperating agents publication-title: IEEE Trans Syst Man Cybern B – year: 2022 ident: bib0028 article-title: Artificial hummingbird algorithm: a new bio-inspired optimizer with its engineering applications publication-title: Comput Method Appl Mech Eng – volume: 27 start-page: 79 year: 2016 end-page: 95 ident: bib0044 article-title: Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems publication-title: Neural Comput Appl – year: 2022 ident: bib0025 article-title: Optimization of an auto drum fashioned brake using the elite opposition-based learning and chaotic k-best gravitational search strategy based grey wolf optimizer algorithm publication-title: Appl Soft Comput – volume: 8 start-page: 1 year: 2016 end-page: 22 ident: bib0036 article-title: Lévy-flight moth-flame algorithm for function optimization and engineering design problems publication-title: Math Probl Eng – volume: 38 start-page: 2228 year: 2021 end-page: 2251 ident: bib0002 article-title: An adaptive resistance and stamina strategy-based dragonfly algorithm for solving engineering optimization problems publication-title: Eng Comput – volume: 77 start-page: 425 year: 2007 end-page: 491 ident: bib0013 article-title: Central force optimization publication-title: Prog Electromagn Res – volume: 57 start-page: 211 year: 2021 end-page: 223 ident: bib0005 article-title: Multi-objective optimization of bucket wheel reclaimer based on improved dragonfly algorithm publication-title: Jixie Gongcheng Xuebao/J Mech Eng – volume: 11 start-page: 34 year: 1997 end-page: 359 ident: bib0009 article-title: Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces publication-title: J Glob Optim – volume: 655 start-page: 1 year: 2016 end-page: 70 ident: bib0031 article-title: Modern meta-heuristics based on nonlinear physics processes: a review of models and design procedures publication-title: Phys Rep – volume: 59 start-page: 134 year: 2018 end-page: 139 ident: bib0034 article-title: Similarity of muscle synergies extracted from the lower limb including the deep muscles between level and uphill treadmill walking publication-title: Gait Posture – volume: 110 start-page: 151 year: 2012 end-page: 166 ident: bib0052 article-title: Water cycle algorithm-a novel metaheuristic optimization method for solving constrained engineering optimization problems publication-title: Comput Struct – volume: 13 start-page: 398 year: 2009 end-page: 417 ident: bib0042 article-title: Differential evolution algorithm with strategy adaptation for global numerical optimization publication-title: IEEE Trans Evol Comput – volume: 179 start-page: 2232 year: 2009 end-page: 2248 ident: bib0011 article-title: GSA: a gravitational search algorithm publication-title: Inf Sci – volume: 42 start-page: 233 year: 2007 end-page: 250 ident: bib0055 article-title: Optimum design of rolling element bearings using genetic algorithms publication-title: Mech Mach Theory – volume: 29 start-page: 17 year: 2013 end-page: 35 ident: bib0047 article-title: Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems publication-title: Eng Comput – volume: 109 year: 2021 ident: bib0029 article-title: Nonlinear-based chaotic harris hawks optimizer: algorithm and internet of vehicles application publication-title: Appl Soft Comput – volume: 29 start-page: 17 year: 2013 end-page: 35 ident: bib0010 article-title: Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems publication-title: Eng Comput – year: 2022 ident: bib0027 article-title: Binary Simulated Normal Distribution Optimizer for feature selection: theory and application in COVID-19 datasets publication-title: Expert Syst Appl – start-page: 24 year: 2021 end-page: 50 ident: bib0026 article-title: Multi-objective equilibrium optimizer: framework and development for solving multi-objective optimization problems publication-title: J Comput Des Eng – year: 2010 ident: bib0035 article-title: Nature-inspired metaheuristic algorithms – volume: 10 start-page: 629 year: 2010 end-page: 640 ident: bib0050 article-title: Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization publication-title: Appl Soft Comput – volume: 267 start-page: 66 year: 1992 end-page: 73 ident: bib0006 article-title: Genetic algorithms publication-title: Sci Am – volume: 40 start-page: 3951 year: 2016 end-page: 3978 ident: bib0054 article-title: Passing vehicle search (pvs): a novel metaheuristic algorithm publication-title: Appl Math Model – start-page: 39 year: 1995 end-page: 43 ident: bib0008 article-title: A new optimizer using particle swarm theory publication-title: Proceedings of the sixth international symposium on micro machine and human science, MHS’95 – volume: 47 start-page: 2652 year: 2016 end-page: 2670 ident: bib0037 article-title: Lévy flight artificial bee colony algorithm publication-title: Int J Syst Sci – volume: 87 year: 2020 ident: bib0061 article-title: Manta ray foraging optimization: an effective bio-inspired optimizer for engineering applications publication-title: Eng Appl Artif Intell – volume: 11 start-page: 1 year: 2003 end-page: 18 ident: bib0043 article-title: Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES) publication-title: Evol Comput – volume: 183 start-page: 1 year: 2012 end-page: 15 ident: bib0014 article-title: Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems publication-title: Inf Sci – volume: 83 start-page: 80 year: 2015 end-page: 98 ident: bib0040 article-title: The ant lion optimizer publication-title: Adv Eng Softw – volume: 39 start-page: 459 year: 2007 end-page: 471 ident: bib0007 article-title: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm publication-title: J Glob Optim – volume: 41 start-page: 947 year: 2010 end-page: 963 ident: bib0058 article-title: An effective differential evolution with level comparison for constrained engineering design publication-title: Struct Multidiscip Optim – volume: 99 start-page: 1 year: 2020 end-page: 7 ident: bib0017 article-title: Experiment-based approach to teach optimization techniques publication-title: IEEE Trans Educ – volume: 14 start-page: 1042 year: 2021 end-page: 1052 ident: bib0020 article-title: Slime mould algorithm-based tuning of cost-effective fuzzy controllers for servo systems publication-title: Int J Comput Int Sys – volume: 37 start-page: 399 year: 2005 end-page: 409 ident: bib0048 article-title: Global optimization of nonlinear fractional programming problems in engineering design publication-title: Eng Optim – volume: 37 start-page: 395 year: 2009 end-page: 413 ident: bib0056 article-title: Constrained optimization based on hybrid evolutionary algorithm and adaptive constraint-handling technique publication-title: Struct Multidiscip Optim – volume: 388 year: 2022 ident: bib0051 article-title: Artificial hummingbird algorithm: a new bio-inspired optimizer with its engineering applications publication-title: Comput Methods Appl Mech Eng – volume: 27 start-page: 79 issue: 4 year: 2016 ident: 10.1016/j.advengsoft.2022.103158_bib0044 article-title: Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems publication-title: Neural Comput Appl – volume: 40 start-page: 3951 year: 2016 ident: 10.1016/j.advengsoft.2022.103158_bib0054 article-title: Passing vehicle search (pvs): a novel metaheuristic algorithm publication-title: Appl Math Model doi: 10.1016/j.apm.2015.10.040 – volume: 324 start-page: 217 year: 2015 ident: 10.1016/j.advengsoft.2022.103158_bib0004 article-title: Heat transfer search (HTS): a novel optimization algorithm publication-title: Inform Sci doi: 10.1016/j.ins.2015.06.044 – volume: 80 start-page: 52 year: 2016 ident: 10.1016/j.advengsoft.2022.103158_bib0038 article-title: Automatic generation control of a multi-area system using ant lion optimizer algorithm based PID plus second order derivative controller publication-title: Int J Electr Power Energy Syst doi: 10.1016/j.ijepes.2016.01.037 – volume: 83 start-page: 80 year: 2015 ident: 10.1016/j.advengsoft.2022.103158_bib0040 article-title: The ant lion optimizer publication-title: Adv Eng Softw doi: 10.1016/j.advengsoft.2015.01.010 – volume: 105 start-page: 30 year: 2017 ident: 10.1016/j.advengsoft.2022.103158_bib0046 article-title: Grasshopper optimisation algorithm: theory and application publication-title: Adv Eng Softw doi: 10.1016/j.advengsoft.2017.01.004 – volume: 42 start-page: 233 issue: 2 year: 2007 ident: 10.1016/j.advengsoft.2022.103158_bib0055 article-title: Optimum design of rolling element bearings using genetic algorithms publication-title: Mech Mach Theory doi: 10.1016/j.mechmachtheory.2006.02.004 – volume: 19 start-page: 1213 year: 2014 ident: 10.1016/j.advengsoft.2022.103158_bib0030 article-title: Bird mating optimizer: an optimization algorithm inspired by bird mating strategies publication-title: Commun Nonlinear Sci Numer Simul doi: 10.1016/j.cnsns.2013.08.027 – issue: 123 year: 2022 ident: 10.1016/j.advengsoft.2022.103158_bib0025 article-title: Optimization of an auto drum fashioned brake using the elite opposition-based learning and chaotic k-best gravitational search strategy based grey wolf optimizer algorithm publication-title: Appl Soft Comput – volume: 29 start-page: 17 year: 2013 ident: 10.1016/j.advengsoft.2022.103158_bib0047 article-title: Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems publication-title: Eng Comput doi: 10.1007/s00366-011-0241-y – volume: 388 year: 2022 ident: 10.1016/j.advengsoft.2022.103158_bib0051 article-title: Artificial hummingbird algorithm: a new bio-inspired optimizer with its engineering applications publication-title: Comput Methods Appl Mech Eng doi: 10.1016/j.cma.2021.114194 – volume: 57 start-page: 211 issue: 6 year: 2021 ident: 10.1016/j.advengsoft.2022.103158_bib0005 article-title: Multi-objective optimization of bucket wheel reclaimer based on improved dragonfly algorithm publication-title: Jixie Gongcheng Xuebao/J Mech Eng doi: 10.3901/JME.2021.06.211 – volume: 10 start-page: 629 year: 2010 ident: 10.1016/j.advengsoft.2022.103158_bib0050 article-title: Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2009.08.031 – volume: 11 start-page: 25012 issue: 2 year: 2021 ident: 10.1016/j.advengsoft.2022.103158_bib0021 article-title: An adaptive instinctive reaction strategy based on Harris hawks optimization algorithm for numerical optimization problems publication-title: AIP Adv doi: 10.1063/5.0035635 – volume: 8 start-page: 1 year: 2016 ident: 10.1016/j.advengsoft.2022.103158_bib0036 article-title: Lévy-flight moth-flame algorithm for function optimization and engineering design problems publication-title: Math Probl Eng – volume: 26 start-page: 29 year: 1996 ident: 10.1016/j.advengsoft.2022.103158_bib0012 article-title: Ant system: optimization by a colony of cooperating agents publication-title: IEEE Trans Syst Man Cybern B doi: 10.1109/3477.484436 – volume: 41 start-page: 947 issue: 6 year: 2010 ident: 10.1016/j.advengsoft.2022.103158_bib0058 article-title: An effective differential evolution with level comparison for constrained engineering design publication-title: Struct Multidiscip Optim doi: 10.1007/s00158-009-0454-5 – volume: 162 start-page: 267 year: 2019 ident: 10.1016/j.advengsoft.2022.103158_bib0019 article-title: Combined Model-free adaptive control with fuzzy component by virtual reference feedback tuning for tower crane systems publication-title: Proced Comput Sci doi: 10.1016/j.procs.2019.11.284 – volume: 179 start-page: 2232 year: 2009 ident: 10.1016/j.advengsoft.2022.103158_bib0011 article-title: GSA: a gravitational search algorithm publication-title: Inf Sci doi: 10.1016/j.ins.2009.03.004 – start-page: 300 issue: 111 year: 2020 ident: 10.1016/j.advengsoft.2022.103158_bib0024 article-title: Slime mould algorithm: a new method for stochastic optimization publication-title: Future Gener Comp Syst doi: 10.1016/j.future.2020.03.055 – volume: 52 start-page: 915 issue: 6 year: 2020 ident: 10.1016/j.advengsoft.2022.103158_bib0001 article-title: Optimization of a frame structure using the Coulomb force search strategy-based dragonfly algorithm publication-title: Eng Optim doi: 10.1080/0305215X.2019.1618290 – volume: 97 start-page: 849 year: 2019 ident: 10.1016/j.advengsoft.2022.103158_bib0003 article-title: Harris hawks optimization: algorithm and applications publication-title: Future Gener Comput Syst doi: 10.1016/j.future.2019.02.028 – volume: 37 start-page: 395 issue: 4 year: 2009 ident: 10.1016/j.advengsoft.2022.103158_bib0056 article-title: Constrained optimization based on hybrid evolutionary algorithm and adaptive constraint-handling technique publication-title: Struct Multidiscip Optim doi: 10.1007/s00158-008-0238-3 – volume: 40 start-page: 3370 issue: 9 year: 2013 ident: 10.1016/j.advengsoft.2022.103158_bib0059 article-title: Investigating multi-view differential evolution for solving constrained engineering design problems publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2012.12.045 – volume: 29 start-page: 17 year: 2013 ident: 10.1016/j.advengsoft.2022.103158_bib0010 article-title: Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems publication-title: Eng Comput doi: 10.1007/s00366-011-0241-y – issue: 388 year: 2022 ident: 10.1016/j.advengsoft.2022.103158_bib0028 article-title: Artificial hummingbird algorithm: a new bio-inspired optimizer with its engineering applications publication-title: Comput Method Appl Mech Eng – volume: 96 start-page: 156 issue: 15 year: 2016 ident: 10.1016/j.advengsoft.2022.103158_bib0033 article-title: Multiple learning particle swarm optimization with space transformation perturbation and its application in ethylene cracking furnace optimization publication-title: Knowl Based Syst doi: 10.1016/j.knosys.2015.12.020 – volume: 267 start-page: 66 year: 1992 ident: 10.1016/j.advengsoft.2022.103158_bib0006 article-title: Genetic algorithms publication-title: Sci Am doi: 10.1038/scientificamerican0792-66 – volume: 87 issue: 1 year: 2020 ident: 10.1016/j.advengsoft.2022.103158_bib0061 article-title: Manta ray foraging optimization: an effective bio-inspired optimizer for engineering applications publication-title: Eng Appl Artif Intell – start-page: 24 issue: 1 year: 2021 ident: 10.1016/j.advengsoft.2022.103158_bib0026 article-title: Multi-objective equilibrium optimizer: framework and development for solving multi-objective optimization problems publication-title: J Comput Des Eng – volume: 14 start-page: 1042 issue: 1 year: 2021 ident: 10.1016/j.advengsoft.2022.103158_bib0020 article-title: Slime mould algorithm-based tuning of cost-effective fuzzy controllers for servo systems publication-title: Int J Comput Int Sys doi: 10.2991/ijcis.d.210309.001 – volume: 43 start-page: 303 year: 2011 ident: 10.1016/j.advengsoft.2022.103158_bib0053 article-title: Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems publication-title: Comput Aided Des doi: 10.1016/j.cad.2010.12.015 – volume: 77 start-page: 425 year: 2007 ident: 10.1016/j.advengsoft.2022.103158_bib0013 article-title: Central force optimization publication-title: Prog Electromagn Res doi: 10.2528/PIER07082403 – volume: 33 start-page: 735 year: 2001 ident: 10.1016/j.advengsoft.2022.103158_bib0049 article-title: Engineering design optimization using a swarm with an intelligent information sharing among individuals publication-title: Eng Optim doi: 10.1080/03052150108940941 – issue: 200 year: 2022 ident: 10.1016/j.advengsoft.2022.103158_bib0027 article-title: Binary Simulated Normal Distribution Optimizer for feature selection: theory and application in COVID-19 datasets publication-title: Expert Syst Appl – volume: 89 start-page: 228 year: 2015 ident: 10.1016/j.advengsoft.2022.103158_bib0041 article-title: Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm publication-title: Knowl Based Syst doi: 10.1016/j.knosys.2015.07.006 – volume: 1 start-page: 67 year: 1997 ident: 10.1016/j.advengsoft.2022.103158_bib0032 article-title: No free lunch theorems for optimization publication-title: IEEE Trans Evol Comput doi: 10.1109/4235.585893 – volume: 38 start-page: 2228 issue: 5 year: 2021 ident: 10.1016/j.advengsoft.2022.103158_bib0002 article-title: An adaptive resistance and stamina strategy-based dragonfly algorithm for solving engineering optimization problems publication-title: Eng Comput doi: 10.1108/EC-08-2019-0362 – volume: 47 start-page: 2652 issue: 9–12 year: 2016 ident: 10.1016/j.advengsoft.2022.103158_bib0037 article-title: Lévy flight artificial bee colony algorithm publication-title: Int J Syst Sci – issue: 191 year: 2020 ident: 10.1016/j.advengsoft.2022.103158_bib0023 article-title: Equilibrium optimizer: a novel optimization algorithm publication-title: Knowl Based Syst – volume: 109 year: 2021 ident: 10.1016/j.advengsoft.2022.103158_bib0029 article-title: Nonlinear-based chaotic harris hawks optimizer: algorithm and internet of vehicles application publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2021.107574 – start-page: 39 year: 1995 ident: 10.1016/j.advengsoft.2022.103158_bib0008 article-title: A new optimizer using particle swarm theory – start-page: 1178 year: 2017 ident: 10.1016/j.advengsoft.2022.103158_bib0045 – volume: 110 start-page: 151 year: 2012 ident: 10.1016/j.advengsoft.2022.103158_bib0052 article-title: Water cycle algorithm-a novel metaheuristic optimization method for solving constrained engineering optimization problems publication-title: Comput Struct doi: 10.1016/j.compstruc.2012.07.010 – volume: 183 start-page: 1 year: 2012 ident: 10.1016/j.advengsoft.2022.103158_bib0014 article-title: Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems publication-title: Inf Sci doi: 10.1016/j.ins.2011.08.006 – volume: 99 start-page: 1 year: 2020 ident: 10.1016/j.advengsoft.2022.103158_bib0017 article-title: Experiment-based approach to teach optimization techniques publication-title: IEEE Trans Educ – volume: 13 start-page: 398 issue: 2 year: 2009 ident: 10.1016/j.advengsoft.2022.103158_bib0042 article-title: Differential evolution algorithm with strategy adaptation for global numerical optimization publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2008.927706 – volume: 11 start-page: 1 issue: 1 year: 2003 ident: 10.1016/j.advengsoft.2022.103158_bib0043 article-title: Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES) publication-title: Evol Comput doi: 10.1162/106365603321828970 – year: 2010 ident: 10.1016/j.advengsoft.2022.103158_bib0035 – volume: 37 start-page: 399 year: 2005 ident: 10.1016/j.advengsoft.2022.103158_bib0048 article-title: Global optimization of nonlinear fractional programming problems in engineering design publication-title: Eng Optim doi: 10.1080/03052150500066737 – volume: 18 start-page: 1 issue: 1 year: 2020 ident: 10.1016/j.advengsoft.2022.103158_bib0016 article-title: A hybrid swarm algorithm for collective construction of 3d structures publication-title: Int J Artif Intell – volume: 655 start-page: 1 year: 2016 ident: 10.1016/j.advengsoft.2022.103158_bib0031 article-title: Modern meta-heuristics based on nonlinear physics processes: a review of models and design procedures publication-title: Phys Rep doi: 10.1016/j.physrep.2016.08.001 – volume: 39 start-page: 459 year: 2007 ident: 10.1016/j.advengsoft.2022.103158_bib0007 article-title: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm publication-title: J Glob Optim doi: 10.1007/s10898-007-9149-x – volume: 7 start-page: 23 issue: 3 year: 2016 ident: 10.1016/j.advengsoft.2022.103158_bib0018 article-title: Reinforcement learning with particle swarm optimization policy (pso-p) in continuous state and action spaces publication-title: Int J Swarm Intell Res doi: 10.4018/IJSIR.2016070102 – volume: 7 start-page: 80570 year: 2019 ident: 10.1016/j.advengsoft.2022.103158_bib0022 article-title: An improved rider optimization algorithm for solving engineering optimization problems publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2923468 – volume: 10 start-page: 629 issue: 2 year: 2010 ident: 10.1016/j.advengsoft.2022.103158_bib0057 article-title: Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2009.08.031 – volume: 11 start-page: 34 year: 1997 ident: 10.1016/j.advengsoft.2022.103158_bib0009 article-title: Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces publication-title: J Glob Optim doi: 10.1023/A:1008202821328 – volume: 42 start-page: 1418 year: 2007 ident: 10.1016/j.advengsoft.2022.103158_bib0060 article-title: Multi-objective design optimisation of rolling bearings using genetic algorithms publication-title: Mech Mach Theory doi: 10.1016/j.mechmachtheory.2006.10.002 – volume: 59 start-page: 134 year: 2018 ident: 10.1016/j.advengsoft.2022.103158_bib0034 article-title: Similarity of muscle synergies extracted from the lower limb including the deep muscles between level and uphill treadmill walking publication-title: Gait Posture doi: 10.1016/j.gaitpost.2017.10.007 – volume: 16 start-page: 28 year: 2014 ident: 10.1016/j.advengsoft.2022.103158_bib0039 article-title: Modified teaching-learning-based optimization algorithm for global numerical optimization-a comparative study publication-title: Swarm Evol Comput doi: 10.1016/j.swevo.2013.12.005 – volume: 65 start-page: 87 year: 2017 ident: 10.1016/j.advengsoft.2022.103158_bib0015 article-title: Particle swarm optimization for generating interpretable fuzzy reinforcement learning policies publication-title: Eng Appl Artif Intell doi: 10.1016/j.engappai.2017.07.005 |
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