A fitness-based adaptive differential evolution algorithm
The performance of differential evolution (DE) mainly depends on its breeding offspring strategy (i.e., trial vector generation strategies and associated control parameters). To take full advantage of several effective breeding offspring strategies proposed in recent years, a fitness-based adaptive...
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| Vydané v: | Information sciences Ročník 549; s. 116 - 141 |
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Elsevier Inc
01.03.2021
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| ISSN: | 0020-0255, 1872-6291 |
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| Abstract | The performance of differential evolution (DE) mainly depends on its breeding offspring strategy (i.e., trial vector generation strategies and associated control parameters). To take full advantage of several effective breeding offspring strategies proposed in recent years, a fitness-based adaptive differential evolution algorithm (FADE) is proposed in this paper. In FADE, the entire population is split into multiple small-sized swarms, and three popular breeding strategies are saved in an archive which can be utilized by the multiple swarms. In each generation, different individuals in a same swarm adaptively select their own breeding strategy from the archive based on their fitness. With the adaptive breeding strategy, the individuals in a same swarm can exhibit distinct search behaviors. Moreover, the population size can be adaptively adjusted during the evolutionary process according to the performance of the best individual. Based on the adaptive population size, computational resources can be rationally assigned in different evolutionary stages, and then to satisfy diverse requirements of different fitness landscapes. The comprehensive performance of FADE is extensively evaluated by comparisons between it and other eight state-of-art DE variants based on CEC2013 and CEC2017 test suites as well as seven real applications. In addition, the effectiveness and efficiency of the newly introduced adaptive strategies are further confirmed by a set of experiments. |
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| AbstractList | The performance of differential evolution (DE) mainly depends on its breeding offspring strategy (i.e., trial vector generation strategies and associated control parameters). To take full advantage of several effective breeding offspring strategies proposed in recent years, a fitness-based adaptive differential evolution algorithm (FADE) is proposed in this paper. In FADE, the entire population is split into multiple small-sized swarms, and three popular breeding strategies are saved in an archive which can be utilized by the multiple swarms. In each generation, different individuals in a same swarm adaptively select their own breeding strategy from the archive based on their fitness. With the adaptive breeding strategy, the individuals in a same swarm can exhibit distinct search behaviors. Moreover, the population size can be adaptively adjusted during the evolutionary process according to the performance of the best individual. Based on the adaptive population size, computational resources can be rationally assigned in different evolutionary stages, and then to satisfy diverse requirements of different fitness landscapes. The comprehensive performance of FADE is extensively evaluated by comparisons between it and other eight state-of-art DE variants based on CEC2013 and CEC2017 test suites as well as seven real applications. In addition, the effectiveness and efficiency of the newly introduced adaptive strategies are further confirmed by a set of experiments. |
| Author | Wu, Hongrun Zhang, Yinglong Yu, Fei Xu, Xing He, Guoliang Gui, Ling Xia, Xuewen Li, Kangshun Li, Yuanxiang Wei, Bo |
| Author_xml | – sequence: 1 givenname: Xuewen surname: Xia fullname: Xia, Xuewen email: xwxia@whu.edu.cn organization: College of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China – sequence: 2 givenname: Ling surname: Gui fullname: Gui, Ling organization: College of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China – sequence: 3 givenname: Yinglong surname: Zhang fullname: Zhang, Yinglong email: Zhang_yinglong@126.com organization: College of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China – sequence: 4 givenname: Xing surname: Xu fullname: Xu, Xing organization: College of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China – sequence: 5 givenname: Fei surname: Yu fullname: Yu, Fei organization: College of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China – sequence: 6 givenname: Hongrun surname: Wu fullname: Wu, Hongrun organization: College of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China – sequence: 7 givenname: Bo surname: Wei fullname: Wei, Bo organization: School of Informatics Science and Technology, Zhejiang Sci-Tech University, Hangzhou, China – sequence: 8 givenname: Guoliang surname: He fullname: He, Guoliang organization: School of Computer, Wuhan University, Wuhan, China – sequence: 9 givenname: Yuanxiang surname: Li fullname: Li, Yuanxiang organization: College of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China – sequence: 10 givenname: Kangshun surname: Li fullname: Li, Kangshun organization: College of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China |
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| Cites_doi | 10.1016/j.asoc.2014.01.038 10.1007/s00500-016-2418-1 10.1109/TCYB.2017.2710626 10.1109/TEVC.2013.2297160 10.1109/TEVC.2010.2087271 10.1016/j.asoc.2017.06.002 10.1109/ACCESS.2017.2773825 10.1007/s10489-018-1255-6 10.1016/j.ins.2017.02.055 10.1007/s00500-018-3015-2 10.1016/j.ins.2017.09.053 10.1016/j.ins.2018.11.021 10.1016/j.ins.2016.10.003 10.1016/j.ins.2017.09.002 10.1016/j.swevo.2020.100731 10.1109/TII.2016.2535347 10.1109/TEVC.2009.2014613 10.1016/j.asoc.2018.02.042 10.1007/s00500-017-2777-2 10.1016/j.ins.2018.02.048 10.1109/CEC.2016.7744190 10.1016/j.ins.2012.09.019 10.1016/j.swevo.2011.02.002 10.1109/TCYB.2015.2512942 10.1109/TEVC.2014.2360890 10.1109/TEVC.2013.2281528 10.1016/j.swevo.2016.01.004 10.1109/TCYB.2016.2617301 10.1109/TEVC.2008.927706 10.1109/TEVC.2006.872133 10.1109/CEC.2006.1688555 10.1016/j.ins.2010.10.009 10.1016/j.ins.2015.09.009 10.1109/TSMCC.2012.2212007 10.1023/A:1008202821328 10.1016/j.ins.2011.09.001 10.1109/TCYB.2013.2279211 10.1109/CEC.2006.1688285 |
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| References | Brest, Greiner, Bosković (b0015) 2006; 10 Wang, Ren, Li (b0185) 2018; 22 Gämperle, Muller, Koumoutsakos (b0060) 2002 Yu, Shen, Chen (b0210) 2014; 44 Cai, Liao, Wang (b0025) 2018; 433–434 Wu, Shen, Li (b0200) 2018; 423 V.L. Huang, A.K. Qin, P.N. Suganthan, Self-adaptive differential evolution algorithm for constrained real-parameter optimization, in: Proc. of IEEE Congress on Evolutionary Computation, CEC’06, Vancouver, BC, Canada, 2006, pp. 17–24. Ghosh, Das, Zafar (b0070) 2012; 42 Pan, Wang, Gao (b0120) 2011; 181 Derrac, García, Molina (b0050) 2011; 1 Price, Storn (b0125) 2005 Gui, Xia, Yu (b0075) 2019; 50 Awad, Ali, Liang (b0010) 2016 R. Mendes, I. Rocha, E.C. Ferreira et al., A comparison of algorithms for the optimization of fermentation processes, in: Proc. of IEEE Congress on Evolutionary Computation, CEC’06, Vancouver, BC, Canada, 2006, pp. 2018–2025. Cui, Li, Zhu (b0035) 2019; 23 Tang, Dong, Liu (b0150) 2015; 19 Wei, Xia, Yu (b0190) 2020; 57 Du, Leung, Tang (b0055) 2017; 47 G.H. Wu, R. Mallipeddi, P.N. Suganthan et al., Differential evolution with multi population based ensemble of mutation strategies, Inf. Sci. 329(C)(2016) 329–345. Tian, Gao (b0160) 2019; 478 Mohamed, Hadi, Jambi (b0115) 2019; 50 Wang, Cai, Zhang (b0170) 2011; 15 Tian, Li, Yan (b0155) 2019; 49 Zhou, Zhang (b0235) 2017; 47 Ali, Awad, Suganthan (b0005) 2017; 47 Guo, Yang (b0080) 2015; 19 J.J. Liang, B.Y. Qu, P.N. Suganthan, Problem definitions and evaluation criteria for the CEC 2013 special session on real-parameter optimization, Nanyang Technological Univ., Singapore, Tech. Rep., 2013. Das, Mullick, Suganthan (b0045) 2016; 27 Wang, Cai, Zhang (b0175) 2012; 185 Wang, Li, Huang (b0180) 2014; 18 Sarker, Elsayed, Ray (b0135) 2014; 18 G. Sun, Y.Q. Cai, T. Wang et al., Differential evolution with individual-dependent topology adaptation, Inf. Sci. 450(2018), 1–38. Cai, Sun, Wang (b0020) 2017; 59 Zheng, Zhang, Tang (b0230) 2017; 399 Mezura-Montes, Velázquez-Reyes, Coello (b0105) 2006 Xia, Gui, Zhan (b0205) 2018; 67 D. Zaharie, Control of population diversity and adaption in differential evolution algorithms, in: Proc. of Mendel 2003, Ninth International Conference on Soft Computing, 2003, pp. 41–46. Das, Suganthan (b0040) 2010 Zhu, Tang, Fang (b0240) 2013; 223 Storn, Price (b0140) 1997; 11 Qin, Huang, Suganthan (b0130) 2009; 13 Z.Z. Liu, Y. Wang, S.X. Yang et al., Differential evolution with a two-stage optimization mechanism for numerical optimization, in: Proc. of IEEE Congress on Evolutionary Computation, CEC’16, Vancouver, BC, Canada, 2016, pp. 3170–3177. Cui, Li, Zhu (b0030) 2018; 422 Ghosh, Das, Mallipeddi (b0065) 2017 Mohamed, Suganthan (b0110) 2018; 22 Tian, Gao (b0165) 2019; 50 Zhang, Sanderson (b0220) 2009; 13 Zheng, Zhang, Zheng (b0225) 2016; 12 Ali (10.1016/j.ins.2020.11.015_b0005) 2017; 47 Pan (10.1016/j.ins.2020.11.015_b0120) 2011; 181 10.1016/j.ins.2020.11.015_b0095 Ghosh (10.1016/j.ins.2020.11.015_b0065) 2017 10.1016/j.ins.2020.11.015_b0090 Wang (10.1016/j.ins.2020.11.015_b0170) 2011; 15 Mohamed (10.1016/j.ins.2020.11.015_b0115) 2019; 50 Wang (10.1016/j.ins.2020.11.015_b0180) 2014; 18 Xia (10.1016/j.ins.2020.11.015_b0205) 2018; 67 Cui (10.1016/j.ins.2020.11.015_b0030) 2018; 422 Yu (10.1016/j.ins.2020.11.015_b0210) 2014; 44 10.1016/j.ins.2020.11.015_b0195 Wei (10.1016/j.ins.2020.11.015_b0190) 2020; 57 Cai (10.1016/j.ins.2020.11.015_b0025) 2018; 433–434 Zhou (10.1016/j.ins.2020.11.015_b0235) 2017; 47 Du (10.1016/j.ins.2020.11.015_b0055) 2017; 47 Tian (10.1016/j.ins.2020.11.015_b0155) 2019; 49 Wang (10.1016/j.ins.2020.11.015_b0185) 2018; 22 Price (10.1016/j.ins.2020.11.015_b0125) 2005 Qin (10.1016/j.ins.2020.11.015_b0130) 2009; 13 Gui (10.1016/j.ins.2020.11.015_b0075) 2019; 50 Awad (10.1016/j.ins.2020.11.015_b0010) 2016 Sarker (10.1016/j.ins.2020.11.015_b0135) 2014; 18 Mohamed (10.1016/j.ins.2020.11.015_b0110) 2018; 22 Das (10.1016/j.ins.2020.11.015_b0040) 2010 Zhang (10.1016/j.ins.2020.11.015_b0220) 2009; 13 Ghosh (10.1016/j.ins.2020.11.015_b0070) 2012; 42 Cai (10.1016/j.ins.2020.11.015_b0020) 2017; 59 Cui (10.1016/j.ins.2020.11.015_b0035) 2019; 23 Guo (10.1016/j.ins.2020.11.015_b0080) 2015; 19 Zheng (10.1016/j.ins.2020.11.015_b0225) 2016; 12 Derrac (10.1016/j.ins.2020.11.015_b0050) 2011; 1 10.1016/j.ins.2020.11.015_b0100 10.1016/j.ins.2020.11.015_b0145 Brest (10.1016/j.ins.2020.11.015_b0015) 2006; 10 Das (10.1016/j.ins.2020.11.015_b0045) 2016; 27 Zheng (10.1016/j.ins.2020.11.015_b0230) 2017; 399 10.1016/j.ins.2020.11.015_b0085 Wu (10.1016/j.ins.2020.11.015_b0200) 2018; 423 Tian (10.1016/j.ins.2020.11.015_b0165) 2019; 50 Gämperle (10.1016/j.ins.2020.11.015_b0060) 2002 Zhu (10.1016/j.ins.2020.11.015_b0240) 2013; 223 10.1016/j.ins.2020.11.015_b0215 Wang (10.1016/j.ins.2020.11.015_b0175) 2012; 185 Tang (10.1016/j.ins.2020.11.015_b0150) 2015; 19 Mezura-Montes (10.1016/j.ins.2020.11.015_b0105) 2006 Storn (10.1016/j.ins.2020.11.015_b0140) 1997; 11 Tian (10.1016/j.ins.2020.11.015_b0160) 2019; 478 |
| References_xml | – volume: 57 year: 2020 ident: b0190 article-title: Multiple adaptive strategies based particle swarm optimization algorithm publication-title: Swarm Evol. Comput. – volume: 19 start-page: 560 year: 2015 end-page: 574 ident: b0150 article-title: Differential evolution with an individual-dependent mechanism publication-title: IEEE Trans. Evol. Comput. – reference: Z.Z. Liu, Y. Wang, S.X. Yang et al., Differential evolution with a two-stage optimization mechanism for numerical optimization, in: Proc. of IEEE Congress on Evolutionary Computation, CEC’16, Vancouver, BC, Canada, 2016, pp. 3170–3177. – volume: 50 year: 2019 ident: b0115 article-title: Novel mutation strategy for enhancing SHADE and LSHADE algorithms for global numerical optimization, Swarm publication-title: Evol. Comput. – volume: 13 start-page: 398 year: 2009 end-page: 417 ident: b0130 article-title: Differential evolution algorithm with strategy adaptation for global numerical optimization publication-title: IEEE Trans. Evol. Comput. – volume: 10 start-page: 646 year: 2006 end-page: 657 ident: b0015 article-title: Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems publication-title: IEEE Trans. Evol. Comput. – volume: 23 start-page: 3643 year: 2019 end-page: 3660 ident: b0035 article-title: Differential evolution algorithm with dichotomy-based parameter space compression publication-title: Soft Comput. – volume: 13 start-page: 945 year: 2009 end-page: 958 ident: b0220 article-title: JADE: adaptive differential evolution with optional external archive publication-title: IEEE Trans. Evol. Comput. – volume: 12 start-page: 911 year: 2016 end-page: 923 ident: b0225 article-title: Differential evolution algorithm with two-step subpopulation strategy and its application in microwave circuit designs publication-title: IEEE Trans. Ind. Inf. – reference: D. Zaharie, Control of population diversity and adaption in differential evolution algorithms, in: Proc. of Mendel 2003, Ninth International Conference on Soft Computing, 2003, pp. 41–46. – volume: 399 start-page: 13 year: 2017 end-page: 29 ident: b0230 article-title: Differential evolution powered by collective information publication-title: Inf. Sci. – volume: 47 start-page: 2768 year: 2017 end-page: 2779 ident: b0005 article-title: An adaptive multipopulation differential evolution with dynamic population reduction publication-title: IEEE Trans. Cybern. – start-page: 293 year: 2002 end-page: 298 ident: b0060 article-title: A parameter study for differential evolution publication-title: Proc. of Advances Intelligent Systerms Fuzzy Systerms – volume: 22 start-page: 3215 year: 2018 end-page: 3235 ident: b0110 article-title: Real-parameter unconstrained optimization based on enhanced fitness-adaptive differential evolution algorithm with novel mutation publication-title: Soft Comput. – volume: 18 start-page: 232 year: 2014 end-page: 247 ident: b0180 article-title: Differential evolution based on covariance matrix learning and bimodal distribution parameter setting publication-title: Appl. Soft Comput. – start-page: 26944 year: 2017 end-page: 26964 ident: b0065 article-title: A modified differential evolution with distance-based selection for continuous optimization in presence of noise publication-title: IEEE Access – volume: 15 start-page: 55 year: 2011 end-page: 67 ident: b0170 article-title: Differential evolution with composite trial vector generation strategies and control parameters publication-title: IEEE Trans. Evol. Comput. – year: 2010 ident: b0040 article-title: Problem definitions and evaluation criteria for CEC 2011 competition on testing evolutionary algorithms on real world optimization problems – volume: 18 start-page: 689 year: 2014 end-page: 707 ident: b0135 article-title: Differential evolution with dynamic parameters selection for optimization problems publication-title: IEEE Trans. Evol. Comput. – volume: 42 start-page: 1613 year: 2012 end-page: 1623 ident: b0070 article-title: Adaptive-differential-evolution-based design of two-channel quadrature mirror filter banks for sub-band coding and data transmission publication-title: IEEE Trans. Syst., Man, Cybern. C, Appl. Rev. – volume: 181 start-page: 668 year: 2011 end-page: 685 ident: b0120 article-title: An effective hybrid discrete differential evolution algorithm for the flow shop scheduling with intermediate buffers publication-title: Inf. Sci. – volume: 223 start-page: 164 year: 2013 end-page: 191 ident: b0240 article-title: Adaptive population tuning scheme for differential evolution publication-title: Inf. Sci. – volume: 422 start-page: 122 year: 2018 end-page: 143 ident: b0030 article-title: Adaptive multiple-elites-guided composite differential evolution algorithm with a shift mechanism publication-title: Inf. Sci. – volume: 27 start-page: 1 year: 2016 end-page: 30 ident: b0045 article-title: Recent advances in differential evolution - an updated survey publication-title: Swarm Evol. Comput. – reference: V.L. Huang, A.K. Qin, P.N. Suganthan, Self-adaptive differential evolution algorithm for constrained real-parameter optimization, in: Proc. of IEEE Congress on Evolutionary Computation, CEC’06, Vancouver, BC, Canada, 2006, pp. 17–24. – volume: 50 year: 2019 ident: b0165 article-title: An improved differential evolution with information intercrossing and sharing mechanism for numerical optimization, Swarm publication-title: Evol. Comput. – reference: G.H. Wu, R. Mallipeddi, P.N. Suganthan et al., Differential evolution with multi population based ensemble of mutation strategies, Inf. Sci. 329(C)(2016) 329–345. – year: 2016 ident: b0010 article-title: Problem definitions and evaluation criteria for the CEC 2017 special session and competition on single objective real-parameter numerical optimization, Nanyang Technological Univ., Singapore publication-title: Tech. Rep. – reference: G. Sun, Y.Q. Cai, T. Wang et al., Differential evolution with individual-dependent topology adaptation, Inf. Sci. 450(2018), 1–38. – volume: 1 start-page: 3 year: 2011 end-page: 18 ident: b0050 article-title: A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms publication-title: Swarm Evol. Comput. – volume: 44 start-page: 1080 year: 2014 end-page: 1099 ident: b0210 article-title: Differential evolution with two-level parameter adaptation publication-title: IEEE Trans. Cybern. – reference: J.J. Liang, B.Y. Qu, P.N. Suganthan, Problem definitions and evaluation criteria for the CEC 2013 special session on real-parameter optimization, Nanyang Technological Univ., Singapore, Tech. Rep., 2013. – start-page: 485 year: 2006 end-page: 492 ident: b0105 article-title: A comparative study of differential evolution variants for global optimization publication-title: Proc. of the 2006 annual conference on Genetic and Evolutionary Computation GECCO’06, Seattle, Washington, USA – volume: 433–434 start-page: 464 year: 2018 end-page: 509 ident: b0025 article-title: Social learning differential evolution publication-title: Inf. Sci. – volume: 50 year: 2019 ident: b0075 article-title: A multi-role based differential evolution, Swarm publication-title: Evol. Comput. – year: 2005 ident: b0125 article-title: Differential evolution: a practical approach to global optimization – volume: 49 start-page: 628 year: 2019 end-page: 649 ident: b0155 article-title: Differential evolution algorithm directed by individual difference information between generations and current individual information publication-title: Appl. Intel. – volume: 22 start-page: 1313 year: 2018 end-page: 1333 ident: b0185 article-title: APDDE: self-adaptive parameter dynamics differential evolution algorithm publication-title: Soft Comput. – reference: R. Mendes, I. Rocha, E.C. Ferreira et al., A comparison of algorithms for the optimization of fermentation processes, in: Proc. of IEEE Congress on Evolutionary Computation, CEC’06, Vancouver, BC, Canada, 2006, pp. 2018–2025. – volume: 67 start-page: 126 year: 2018 end-page: 140 ident: b0205 article-title: A multi-swarm particle swarm optimization algorithm based on dynamical topology and purposeful detecting publication-title: Appl. Soft Comput. – volume: 47 start-page: 2730 year: 2017 end-page: 2741 ident: b0235 article-title: Abstract convex underestimation assisted multistage differential evolution publication-title: IEEE Trans. Cybern. – volume: 19 start-page: 31 year: 2015 end-page: 49 ident: b0080 article-title: Enhancing differential evolution utilizing eigenvector-based crossover operator publication-title: IEEE Trans. Evol. Comput. – volume: 47 start-page: 244 year: 2017 end-page: 257 ident: b0055 article-title: Differential evolution with event-triggered impulsive control publication-title: IEEE Trans. Cybern. – volume: 11 start-page: 341 year: 1997 end-page: 359 ident: b0140 article-title: Differential evolution: a simple and efficient heuristic for global optimization over continuous spaces publication-title: J. Global Optim. – volume: 185 start-page: 153 year: 2012 end-page: 177 ident: b0175 article-title: Enhancing the search ability of differential evolution through orthogonal crossover publication-title: Inf. Sci. – volume: 59 start-page: 659 year: 2017 end-page: 706 ident: b0020 article-title: Neighborhood-adaptive differential evolution for global numerical optimization publication-title: Appl. Soft Comput. – volume: 478 start-page: 422 year: 2019 end-page: 448 ident: b0160 article-title: Differential evolution with neighborhood-based adaptive evolution mechanism for numerical optimization publication-title: Inf. Sci. – volume: 423 start-page: 172 year: 2018 end-page: 186 ident: b0200 article-title: Ensemble of differential evolution variants publication-title: Inf. Sci. – ident: 10.1016/j.ins.2020.11.015_b0215 – volume: 18 start-page: 232 issue: 1 year: 2014 ident: 10.1016/j.ins.2020.11.015_b0180 article-title: Differential evolution based on covariance matrix learning and bimodal distribution parameter setting publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2014.01.038 – volume: 22 start-page: 1313 year: 2018 ident: 10.1016/j.ins.2020.11.015_b0185 article-title: APDDE: self-adaptive parameter dynamics differential evolution algorithm publication-title: Soft Comput. doi: 10.1007/s00500-016-2418-1 – year: 2005 ident: 10.1016/j.ins.2020.11.015_b0125 – volume: 47 start-page: 2730 issue: 9 year: 2017 ident: 10.1016/j.ins.2020.11.015_b0235 article-title: Abstract convex underestimation assisted multistage differential evolution publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2017.2710626 – volume: 19 start-page: 31 issue: 1 year: 2015 ident: 10.1016/j.ins.2020.11.015_b0080 article-title: Enhancing differential evolution utilizing eigenvector-based crossover operator publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2013.2297160 – volume: 15 start-page: 55 issue: 1 year: 2011 ident: 10.1016/j.ins.2020.11.015_b0170 article-title: Differential evolution with composite trial vector generation strategies and control parameters publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2010.2087271 – volume: 59 start-page: 659 year: 2017 ident: 10.1016/j.ins.2020.11.015_b0020 article-title: Neighborhood-adaptive differential evolution for global numerical optimization publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2017.06.002 – start-page: 26944 year: 2017 ident: 10.1016/j.ins.2020.11.015_b0065 article-title: A modified differential evolution with distance-based selection for continuous optimization in presence of noise publication-title: IEEE Access doi: 10.1109/ACCESS.2017.2773825 – volume: 49 start-page: 628 year: 2019 ident: 10.1016/j.ins.2020.11.015_b0155 article-title: Differential evolution algorithm directed by individual difference information between generations and current individual information publication-title: Appl. Intel. doi: 10.1007/s10489-018-1255-6 – volume: 399 start-page: 13 year: 2017 ident: 10.1016/j.ins.2020.11.015_b0230 article-title: Differential evolution powered by collective information publication-title: Inf. Sci. doi: 10.1016/j.ins.2017.02.055 – volume: 23 start-page: 3643 year: 2019 ident: 10.1016/j.ins.2020.11.015_b0035 article-title: Differential evolution algorithm with dichotomy-based parameter space compression publication-title: Soft Comput. doi: 10.1007/s00500-018-3015-2 – volume: 423 start-page: 172 year: 2018 ident: 10.1016/j.ins.2020.11.015_b0200 article-title: Ensemble of differential evolution variants publication-title: Inf. Sci. doi: 10.1016/j.ins.2017.09.053 – ident: 10.1016/j.ins.2020.11.015_b0090 – start-page: 485 year: 2006 ident: 10.1016/j.ins.2020.11.015_b0105 article-title: A comparative study of differential evolution variants for global optimization – volume: 478 start-page: 422 year: 2019 ident: 10.1016/j.ins.2020.11.015_b0160 article-title: Differential evolution with neighborhood-based adaptive evolution mechanism for numerical optimization publication-title: Inf. Sci. doi: 10.1016/j.ins.2018.11.021 – volume: 433–434 start-page: 464 year: 2018 ident: 10.1016/j.ins.2020.11.015_b0025 article-title: Social learning differential evolution publication-title: Inf. Sci. doi: 10.1016/j.ins.2016.10.003 – volume: 422 start-page: 122 year: 2018 ident: 10.1016/j.ins.2020.11.015_b0030 article-title: Adaptive multiple-elites-guided composite differential evolution algorithm with a shift mechanism publication-title: Inf. Sci. doi: 10.1016/j.ins.2017.09.002 – volume: 57 year: 2020 ident: 10.1016/j.ins.2020.11.015_b0190 article-title: Multiple adaptive strategies based particle swarm optimization algorithm publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2020.100731 – volume: 12 start-page: 911 issue: 3 year: 2016 ident: 10.1016/j.ins.2020.11.015_b0225 article-title: Differential evolution algorithm with two-step subpopulation strategy and its application in microwave circuit designs publication-title: IEEE Trans. Ind. Inf. doi: 10.1109/TII.2016.2535347 – volume: 13 start-page: 945 issue: 5 year: 2009 ident: 10.1016/j.ins.2020.11.015_b0220 article-title: JADE: adaptive differential evolution with optional external archive publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2009.2014613 – volume: 67 start-page: 126 year: 2018 ident: 10.1016/j.ins.2020.11.015_b0205 article-title: A multi-swarm particle swarm optimization algorithm based on dynamical topology and purposeful detecting publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2018.02.042 – volume: 22 start-page: 3215 issue: 10 year: 2018 ident: 10.1016/j.ins.2020.11.015_b0110 article-title: Real-parameter unconstrained optimization based on enhanced fitness-adaptive differential evolution algorithm with novel mutation publication-title: Soft Comput. doi: 10.1007/s00500-017-2777-2 – ident: 10.1016/j.ins.2020.11.015_b0145 doi: 10.1016/j.ins.2018.02.048 – ident: 10.1016/j.ins.2020.11.015_b0095 doi: 10.1109/CEC.2016.7744190 – volume: 223 start-page: 164 year: 2013 ident: 10.1016/j.ins.2020.11.015_b0240 article-title: Adaptive population tuning scheme for differential evolution publication-title: Inf. Sci. doi: 10.1016/j.ins.2012.09.019 – year: 2016 ident: 10.1016/j.ins.2020.11.015_b0010 article-title: Problem definitions and evaluation criteria for the CEC 2017 special session and competition on single objective real-parameter numerical optimization, Nanyang Technological Univ., Singapore publication-title: Tech. Rep. – year: 2010 ident: 10.1016/j.ins.2020.11.015_b0040 – volume: 1 start-page: 3 issue: 1 year: 2011 ident: 10.1016/j.ins.2020.11.015_b0050 article-title: A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2011.02.002 – volume: 47 start-page: 244 issue: 1 year: 2017 ident: 10.1016/j.ins.2020.11.015_b0055 article-title: Differential evolution with event-triggered impulsive control publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2015.2512942 – volume: 19 start-page: 560 issue: 4 year: 2015 ident: 10.1016/j.ins.2020.11.015_b0150 article-title: Differential evolution with an individual-dependent mechanism publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2014.2360890 – volume: 50 year: 2019 ident: 10.1016/j.ins.2020.11.015_b0075 article-title: A multi-role based differential evolution, Swarm publication-title: Evol. Comput. – volume: 18 start-page: 689 issue: 5 year: 2014 ident: 10.1016/j.ins.2020.11.015_b0135 article-title: Differential evolution with dynamic parameters selection for optimization problems publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2013.2281528 – volume: 27 start-page: 1 year: 2016 ident: 10.1016/j.ins.2020.11.015_b0045 article-title: Recent advances in differential evolution - an updated survey publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2016.01.004 – volume: 47 start-page: 2768 issue: 9 year: 2017 ident: 10.1016/j.ins.2020.11.015_b0005 article-title: An adaptive multipopulation differential evolution with dynamic population reduction publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2016.2617301 – volume: 13 start-page: 398 issue: 2 year: 2009 ident: 10.1016/j.ins.2020.11.015_b0130 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: 10 start-page: 646 issue: 6 year: 2006 ident: 10.1016/j.ins.2020.11.015_b0015 article-title: Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2006.872133 – start-page: 293 year: 2002 ident: 10.1016/j.ins.2020.11.015_b0060 article-title: A parameter study for differential evolution – ident: 10.1016/j.ins.2020.11.015_b0100 doi: 10.1109/CEC.2006.1688555 – volume: 181 start-page: 668 issue: 3 year: 2011 ident: 10.1016/j.ins.2020.11.015_b0120 article-title: An effective hybrid discrete differential evolution algorithm for the flow shop scheduling with intermediate buffers publication-title: Inf. Sci. doi: 10.1016/j.ins.2010.10.009 – ident: 10.1016/j.ins.2020.11.015_b0195 doi: 10.1016/j.ins.2015.09.009 – volume: 42 start-page: 1613 issue: 6 year: 2012 ident: 10.1016/j.ins.2020.11.015_b0070 article-title: Adaptive-differential-evolution-based design of two-channel quadrature mirror filter banks for sub-band coding and data transmission publication-title: IEEE Trans. Syst., Man, Cybern. C, Appl. Rev. doi: 10.1109/TSMCC.2012.2212007 – volume: 11 start-page: 341 issue: 4 year: 1997 ident: 10.1016/j.ins.2020.11.015_b0140 article-title: Differential evolution: a simple and efficient heuristic for global optimization over continuous spaces publication-title: J. Global Optim. doi: 10.1023/A:1008202821328 – volume: 50 year: 2019 ident: 10.1016/j.ins.2020.11.015_b0115 article-title: Novel mutation strategy for enhancing SHADE and LSHADE algorithms for global numerical optimization, Swarm publication-title: Evol. Comput. – volume: 185 start-page: 153 issue: 1 year: 2012 ident: 10.1016/j.ins.2020.11.015_b0175 article-title: Enhancing the search ability of differential evolution through orthogonal crossover publication-title: Inf. Sci. doi: 10.1016/j.ins.2011.09.001 – volume: 44 start-page: 1080 issue: 7 year: 2014 ident: 10.1016/j.ins.2020.11.015_b0210 article-title: Differential evolution with two-level parameter adaptation publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2013.2279211 – volume: 50 year: 2019 ident: 10.1016/j.ins.2020.11.015_b0165 article-title: An improved differential evolution with information intercrossing and sharing mechanism for numerical optimization, Swarm publication-title: Evol. Comput. – ident: 10.1016/j.ins.2020.11.015_b0085 doi: 10.1109/CEC.2006.1688285 |
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