Many-objective differential evolution optimization based on reference points: NSDE-R
Design methodologies of today require the solution of several many-objective optimization problems. The last two decades have seen a surge in several algorithms capable of solving multi-objective optimization problems. It was only in the past 5 years that new algorithms capable of coping with a larg...
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| Vydáno v: | Structural and multidisciplinary optimization Ročník 60; číslo 4; s. 1455 - 1473 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.10.2019
Springer Nature B.V |
| Témata: | |
| ISSN: | 1615-147X, 1615-1488 |
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| Abstract | Design methodologies of today require the solution of several many-objective optimization problems. The last two decades have seen a surge in several algorithms capable of solving multi-objective optimization problems. It was only in the past 5 years that new algorithms capable of coping with a large number of objectives have been introduced. This work presents a new differential evolution algorithm (NSDE-R) capable of efficiently solving many-objective optimization problems. The algorithms make use of reference points evenly distributed through the objective function space to preserve diversity and aid in multi-criteria-decision-making. The proposed NSDE-R was applied to test problems from the DTLZ and WFG suite, having three to 15 objectives. Two mutation donor operators were investigated for their ability to converge to the analytical Pareto front while maintaining diversity. The ability of NSDE-R to converge to a user-specified region of the Pareto front is also investigated. The proposed NSDE-R algorithm has shown to have a higher rate of convergence and better convergence to the analytical Pareto front. |
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| AbstractList | Design methodologies of today require the solution of several many-objective optimization problems. The last two decades have seen a surge in several algorithms capable of solving multi-objective optimization problems. It was only in the past 5 years that new algorithms capable of coping with a large number of objectives have been introduced. This work presents a new differential evolution algorithm (NSDE-R) capable of efficiently solving many-objective optimization problems. The algorithms make use of reference points evenly distributed through the objective function space to preserve diversity and aid in multi-criteria-decision-making. The proposed NSDE-R was applied to test problems from the DTLZ and WFG suite, having three to 15 objectives. Two mutation donor operators were investigated for their ability to converge to the analytical Pareto front while maintaining diversity. The ability of NSDE-R to converge to a user-specified region of the Pareto front is also investigated. The proposed NSDE-R algorithm has shown to have a higher rate of convergence and better convergence to the analytical Pareto front. Design methodologies of today require the solution of several many-objective optimization problems. The last two decades have seen a surge in several algorithms capable of solving multi-objective optimization problems. It was only in the past 5 years that new algorithms capable of coping with a large number of objectives have been introduced. This work presents a new differential evolution algorithm (NSDE-R) capable of efficiently solving many-objective optimization problems. The algorithms make use of reference points evenly distributed through the objective function space to preserve diversity and aid in multi-criteria-decision-making. The proposed NSDE-R was applied to test problems from the DTLZ and WFG suite, having three to 15 objectives. Two mutation donor operators were investigated for their ability to converge to the analytical Pareto front while maintaining diversity. The ability of NSDE-R to converge to a user-specified region of the Pareto front is also investigated. The proposed NSDE-R algorithm has shown to have a higher rate of convergence and better convergence to the analytical Pareto front. |
| Author | Reddy, Sohail R. Dulikravich, George S. |
| Author_xml | – sequence: 1 givenname: Sohail R. orcidid: 0000-0001-6882-9737 surname: Reddy fullname: Reddy, Sohail R. email: sredd001@fiu.edu organization: Department of Mechanical and Materials Engineering and Multidisciplinary Analysis, Inverse Design, Robust Optimization and Control - MAIDROC Laboratory, Florida International University – sequence: 2 givenname: George S. surname: Dulikravich fullname: Dulikravich, George S. organization: Department of Mechanical and Materials Engineering and Multidisciplinary Analysis, Inverse Design, Robust Optimization and Control - MAIDROC Laboratory, Florida International University |
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| Cites_doi | 10.1109/TEVC.2013.2281535 10.1007/1-84628-137-7_6 10.1162/EVCO_a_00009 10.1007/s00158-016-1485-3 10.1109/TEVC.2010.2077298 10.1109/TEVC.2005.861417 10.1142/5712 10.1109/4235.797969 10.1109/TEVC.2003.810761 10.1109/TEVC.2016.2592479 10.1108/02644401011022382 10.1137/S1052623496307510 10.1109/TEVC.2014.2373386 10.1109/4235.996017 10.1109/TEVC.2010.2059031 10.1016/j.ins.2016.09.026 10.1109/CEC.2012.6256170 10.1023/A:1008202821328 10.1007/978-3-540-78297-1_1 10.2172/573301 10.1007/s00158-007-0163-x |
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| Copyright | Springer-Verlag GmbH Germany, part of Springer Nature 2019 Structural and Multidisciplinary Optimization is a copyright of Springer, (2019). All Rights Reserved. |
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| Keywords | NSDE-R Differential evolution Reference points Many-objective optimization Evolutionary computation Non-dominated sorting |
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| References | Zitzler, Künzli (CR30) 2004 Fan, Liu, Lampinen (CR16) 2010; 27 Figueiredo, Ludermir, Bastos-Filho (CR17) 2016; 374 Li, Deb, Zhang, Kwong (CR23) 2015; 19 Jiang, Yang (CR21) 2017; 21 While, Bradstreet, Barone (CR28) 2012; 16 Bader, Zitzler (CR2) 2011; 19 Zitzler, Thiele (CR31) 1999; 3 Huband, Hingston, Barone, While (CR19) 2006; 10 Chankong, Haimes (CR4) 1983 Robic, Filipic (CR26) 2005 Deb, Agrawal (CR10) 1994; 9 He, Dai, Chen (CR18) 2014; 2014 CR5 Deb, Goyal (CR11) 1996; 26 Bosman, Thierens (CR3) 2003; 7 CR29 CR9 CR27 CR25 Deb, Pratap, Agarwal, Meyarivan (CR13) 2002; 6 CR24 Das, Suganthan (CR8) 2011; 15 CR22 Bader, Zitzler (CR1) 2011; 19 Deb, Thiele, Laumanns, Zitzler, Abraham, Jain, Goldberg (CR14) 2005 Das, Dennis (CR7) 1998; 8 Inclan, Dulikravich (CR20) 2017; 55 Coello Coello, Lamont (CR6) 2004 Deb, Jain (CR12) 2014; 18 Denysiuk, Costa, Santo (CR15) 2013 S Huband (2272_CR19) 2006; 10 K Li (2272_CR23) 2015; 19 J Bader (2272_CR2) 2011; 19 E Zitzler (2272_CR30) 2004 K Deb (2272_CR11) 1996; 26 EJ Inclan (2272_CR20) 2017; 55 S Das (2272_CR7) 1998; 8 K Deb (2272_CR10) 1994; 9 S Das (2272_CR8) 2011; 15 T Robic (2272_CR26) 2005 2272_CR29 2272_CR27 J Bader (2272_CR1) 2011; 19 2272_CR22 P Bosman (2272_CR3) 2003; 7 K Deb (2272_CR14) 2005 R Denysiuk (2272_CR15) 2013 X He (2272_CR18) 2014; 2014 2272_CR25 2272_CR24 H Fan (2272_CR16) 2010; 27 V Chankong (2272_CR4) 1983 K Deb (2272_CR13) 2002; 6 E Zitzler (2272_CR31) 1999; 3 EMN Figueiredo (2272_CR17) 2016; 374 CA Coello Coello (2272_CR6) 2004 K Deb (2272_CR12) 2014; 18 2272_CR5 S Jiang (2272_CR21) 2017; 21 RL While (2272_CR28) 2012; 16 2272_CR9 |
| References_xml | – ident: CR22 – volume: 18 start-page: 577 issue: 4 year: 2014 end-page: 601 ident: CR12 article-title: An evolutionary many-objective optimization algorithm using reference-point based non-dominated sorting approach, part I: solving problems with box constraints publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2013.2281535 – volume: 26 start-page: 30 year: 1996 end-page: 45 ident: CR11 article-title: A combined genetic adaptive search (GeneAS) for engineering design publication-title: Comput Sci Inform – start-page: 105 year: 2005 end-page: 145 ident: CR14 article-title: Scalable test problems for evolutionary multiobjective optimization publication-title: Evolutionary Multiobjective Optimization, series on advanced information and knowledge processing doi: 10.1007/1-84628-137-7_6 – start-page: 591 year: 2013 end-page: 598 ident: CR15 article-title: Many-objective optimization using differential evolution with variable-wise mutation restriction publication-title: Proceedings of the GECCO’13 – start-page: 520 year: 2005 end-page: 533 ident: CR26 article-title: DEMO: differential evolution for multi- objective optimization publication-title: Proc. 3rd Int. Conf. Evol. Multi-Criterion Optimization, LNCS 3410 – ident: CR29 – ident: CR25 – ident: CR27 – volume: 19 start-page: 45 issue: 1 year: 2011 end-page: 76 ident: CR1 article-title: HypE: an algorithm for fast hypervolume-based many-objective optimization publication-title: Evol Comput doi: 10.1162/EVCO_a_00009 – volume: 55 start-page: 179 issue: 1 year: 2017 end-page: 204 ident: CR20 article-title: Demonstration of effective global optimization techniques via comparative analysis on a large analytical problem set publication-title: Struct Multidiscp Optim doi: 10.1007/s00158-016-1485-3 – volume: 16 start-page: 86 issue: 1 year: 2012 end-page: 95 ident: CR28 article-title: A fast way of calculating exact hypervolumes publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2010.2077298 – volume: 9 start-page: 1 year: 1994 end-page: 34 ident: CR10 article-title: Simulated binary crossover for continuous search space publication-title: Complex Syst – volume: 10 start-page: 477 issue: 5 year: 2006 end-page: 506 ident: CR19 article-title: A review of multiobjective test problems and a scalable test problem toolkit publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2005.861417 – year: 2004 ident: CR6 publication-title: Applications of multi-objective evolutionary algorithms doi: 10.1142/5712 – volume: 3 start-page: 257 issue: 4 year: 1999 end-page: 271 ident: CR31 article-title: Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach publication-title: IEEE Trans- Actions Evol Comput doi: 10.1109/4235.797969 – volume: 7 start-page: 174 issue: 2 year: 2003 end-page: 188 ident: CR3 article-title: The balance between proximity and diversity in multiobjective evolutionary algorithms publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2003.810761 – start-page: 832 year: 2004 end-page: 842 ident: CR30 article-title: Indicator-based selection in multiobjective search publication-title: Proc. 8th Int Conf Parallel Problem Solving from Nature – volume: 2014 start-page: 1 year: 2014 end-page: 8 ident: CR18 article-title: Many-objective optimization using adaptive differential evolution with a new ranking method publication-title: Math Probl Eng – volume: 21 start-page: 329 issue: 3 year: 2017 end-page: 346 ident: CR21 article-title: A strength Pareto evolutionary algorithm based on reference direction for multiobjective and many-objective optimization publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2016.2592479 – volume: 19 start-page: 45 issue: 1 year: 2011 end-page: 76 ident: CR2 article-title: HyPE: an algorithm for fast hypervolume-based many-objective optimization publication-title: Evol Comput doi: 10.1162/EVCO_a_00009 – volume: 27 start-page: 225 year: 2010 end-page: 242 ident: CR16 article-title: Some improvement to the mutation donor of differential evolution publication-title: Eng Comput doi: 10.1108/02644401011022382 – volume: 8 start-page: 631 year: 1998 end-page: 657 ident: CR7 article-title: Normal-boundary intersection: a new method for generating the Pareto surface in nonlinear multicriteria optimization problems publication-title: SIAM J Optim doi: 10.1137/S1052623496307510 – ident: CR9 – volume: 19 start-page: 694 issue: 5 year: 2015 end-page: 716 ident: CR23 article-title: An evolutionary many- objective optimization algorithm based on dominance and decomposition publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2014.2373386 – year: 1983 ident: CR4 publication-title: Multiobjective decision making theory and methodology – ident: CR5 – volume: 6 start-page: 182 issue: 2 year: 2002 end-page: 197 ident: CR13 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Trans Evol Comput doi: 10.1109/4235.996017 – volume: 15 start-page: 4 issue: 1 year: 2011 end-page: 31 ident: CR8 article-title: Differential evolution: a survey of the state-of-the-art publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2010.2059031 – ident: CR24 – volume: 374 start-page: 115 year: 2016 end-page: 134 ident: CR17 article-title: Many objective particle swarm optimization publication-title: Inf Sci doi: 10.1016/j.ins.2016.09.026 – volume: 10 start-page: 477 issue: 5 year: 2006 ident: 2272_CR19 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2005.861417 – ident: 2272_CR25 – volume-title: Multiobjective decision making theory and methodology year: 1983 ident: 2272_CR4 – volume: 3 start-page: 257 issue: 4 year: 1999 ident: 2272_CR31 publication-title: IEEE Trans- Actions Evol Comput doi: 10.1109/4235.797969 – start-page: 832 volume-title: Proc. 8th Int Conf Parallel Problem Solving from Nature year: 2004 ident: 2272_CR30 – volume: 19 start-page: 45 issue: 1 year: 2011 ident: 2272_CR1 publication-title: Evol Comput doi: 10.1162/EVCO_a_00009 – volume: 374 start-page: 115 year: 2016 ident: 2272_CR17 publication-title: Inf Sci doi: 10.1016/j.ins.2016.09.026 – volume: 15 start-page: 4 issue: 1 year: 2011 ident: 2272_CR8 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2010.2059031 – start-page: 520 volume-title: Proc. 3rd Int. Conf. Evol. Multi-Criterion Optimization, LNCS 3410 year: 2005 ident: 2272_CR26 – ident: 2272_CR5 doi: 10.1109/CEC.2012.6256170 – volume: 16 start-page: 86 issue: 1 year: 2012 ident: 2272_CR28 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2010.2077298 – volume: 55 start-page: 179 issue: 1 year: 2017 ident: 2272_CR20 publication-title: Struct Multidiscp Optim doi: 10.1007/s00158-016-1485-3 – start-page: 591 volume-title: Proceedings of the GECCO’13 year: 2013 ident: 2272_CR15 – volume: 19 start-page: 694 issue: 5 year: 2015 ident: 2272_CR23 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2014.2373386 – ident: 2272_CR27 doi: 10.1023/A:1008202821328 – volume-title: Applications of multi-objective evolutionary algorithms year: 2004 ident: 2272_CR6 doi: 10.1142/5712 – ident: 2272_CR22 – volume: 7 start-page: 174 issue: 2 year: 2003 ident: 2272_CR3 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2003.810761 – start-page: 105 volume-title: Evolutionary Multiobjective Optimization, series on advanced information and knowledge processing year: 2005 ident: 2272_CR14 doi: 10.1007/1-84628-137-7_6 – volume: 21 start-page: 329 issue: 3 year: 2017 ident: 2272_CR21 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2016.2592479 – volume: 19 start-page: 45 issue: 1 year: 2011 ident: 2272_CR2 publication-title: Evol Comput doi: 10.1162/EVCO_a_00009 – volume: 27 start-page: 225 year: 2010 ident: 2272_CR16 publication-title: Eng Comput doi: 10.1108/02644401011022382 – volume: 26 start-page: 30 year: 1996 ident: 2272_CR11 publication-title: Comput Sci Inform – volume: 18 start-page: 577 issue: 4 year: 2014 ident: 2272_CR12 publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2013.2281535 – ident: 2272_CR9 doi: 10.1007/978-3-540-78297-1_1 – volume: 9 start-page: 1 year: 1994 ident: 2272_CR10 publication-title: Complex Syst – volume: 6 start-page: 182 issue: 2 year: 2002 ident: 2272_CR13 publication-title: IEEE Trans Evol Comput doi: 10.1109/4235.996017 – ident: 2272_CR29 doi: 10.2172/573301 – volume: 2014 start-page: 1 year: 2014 ident: 2272_CR18 publication-title: Math Probl Eng – volume: 8 start-page: 631 year: 1998 ident: 2272_CR7 publication-title: SIAM J Optim doi: 10.1137/S1052623496307510 – ident: 2272_CR24 doi: 10.1007/s00158-007-0163-x |
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| SubjectTerms | Algorithms Computational Mathematics and Numerical Analysis Convergence Decision making Engineering Engineering Design Evolutionary algorithms Evolutionary computation Function space Multiple criterion Multiple objective analysis Mutation Operators (mathematics) Optimization Research Paper Theoretical and Applied Mechanics |
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| Title | Many-objective differential evolution optimization based on reference points: NSDE-R |
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| Volume | 60 |
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