IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems

Inverted generational distance (IGD) has been widely considered as a reliable performance indicator to concurrently quantify the convergence and diversity of multiobjective and many-objective evolutionary algorithms. In this paper, an IGD indicator-based evolutionary algorithm for solving many-objec...

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Veröffentlicht in:	IEEE transactions on evolutionary computation Jg. 23; H. 2; S. 173 - 187
Hauptverfasser:	Sun, Yanan, Yen, Gary G., Yi, Zhang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.04.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Approximation algorithms Business metrics Convergence Estimation Evolutionary algorithms Evolutionary computation Genetic algorithms Inverted generational distance (IGD) linear assignment problem (LAP) many-objective evolutionary optimization algorithm Multiple objective analysis nadir point Optimization Performance evaluation Performance measurement Sorting
ISSN:	1089-778X, 1941-0026
Online-Zugang:	Volltext
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Abstract	Inverted generational distance (IGD) has been widely considered as a reliable performance indicator to concurrently quantify the convergence and diversity of multiobjective and many-objective evolutionary algorithms. In this paper, an IGD indicator-based evolutionary algorithm for solving many-objective optimization problems (MaOPs) has been proposed. Specifically, the IGD indicator is employed in each generation to select the solutions with favorable convergence and diversity. In addition, a computationally efficient dominance comparison method is designed to assign the rank values of solutions along with three newly proposed proximity distance assignments. Based on these two designs, the solutions are selected from a global view by linear assignment mechanism to concern the convergence and diversity simultaneously. In order to facilitate the accuracy of the sampled reference points for the calculation of IGD indicator, we also propose an efficient decomposition-based nadir point estimation method for constructing the Utopian Pareto front (PF) which is regarded as the best approximate PF for real-world MaOPs at the early stage of the evolution. To evaluate the performance, a series of experiments is performed on the proposed algorithm against a group of selected state-of-the-art many-objective optimization algorithms over optimization problems with 8-, 15-, and 20-objective. Experimental results measured by the chosen performance metrics indicate that the proposed algorithm is very competitive in addressing MaOPs.
AbstractList	Inverted generational distance (IGD) has been widely considered as a reliable performance indicator to concurrently quantify the convergence and diversity of multiobjective and many-objective evolutionary algorithms. In this paper, an IGD indicator-based evolutionary algorithm for solving many-objective optimization problems (MaOPs) has been proposed. Specifically, the IGD indicator is employed in each generation to select the solutions with favorable convergence and diversity. In addition, a computationally efficient dominance comparison method is designed to assign the rank values of solutions along with three newly proposed proximity distance assignments. Based on these two designs, the solutions are selected from a global view by linear assignment mechanism to concern the convergence and diversity simultaneously. In order to facilitate the accuracy of the sampled reference points for the calculation of IGD indicator, we also propose an efficient decomposition-based nadir point estimation method for constructing the Utopian Pareto front (PF) which is regarded as the best approximate PF for real-world MaOPs at the early stage of the evolution. To evaluate the performance, a series of experiments is performed on the proposed algorithm against a group of selected state-of-the-art many-objective optimization algorithms over optimization problems with 8-, 15-, and 20-objective. Experimental results measured by the chosen performance metrics indicate that the proposed algorithm is very competitive in addressing MaOPs.
Author	Yi, Zhang Yen, Gary G. Sun, Yanan
Author_xml	– sequence: 1 givenname: Yanan surname: Sun fullname: Sun, Yanan email: yanan.sun@ecs.vuw.ac.nz organization: College of Computer Science, Sichuan University, Chengdu, China – sequence: 2 givenname: Gary G. orcidid: 0000-0001-8851-5348 surname: Yen fullname: Yen, Gary G. email: gyen@okstate.edu organization: School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, OK, USA – sequence: 3 givenname: Zhang orcidid: 0000-0002-5867-9322 surname: Yi fullname: Yi, Zhang email: zhangyi@scu.edu.cn organization: College of Computer Science, Sichuan University, Chengdu, China
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Cites_doi	10.1016/0167-188X(86)90030-3 10.1109/TEVC.2007.910138 10.1109/TEVC.2010.2093579 10.1109/TEVC.2015.2455812 10.1109/TEVC.2013.2293776 10.1109/CISW.2007.4425478 10.1109/CEC.2007.4424730 10.1109/TSMCB.2008.926329 10.1007/978-3-540-31880-4_5 10.1109/TEVC.2014.2339823 10.1162/evco.2007.15.1.1 10.1109/TEVC.2013.2262178 10.1145/2792984 10.1109/CEC.2017.7969343 10.1007/3-540-36970-8_27 10.1007/978-3-319-15892-1_1 10.1109/TEVC.2015.2420112 10.1109/CEC.2016.7744269 10.1109/TEVC.2015.2424921 10.1109/TEVC.2012.2227145 10.1007/1-84628-137-7_6 10.1109/TCYB.2014.2365354 10.1109/TEVC.2016.2519378 10.1109/TEVC.2007.892759 10.1109/CEC.2014.6900319 10.1109/TSMCB.2012.2231860 10.1007/978-3-642-15871-1_10 10.1109/TEVC.2013.2281535 10.1109/TEVC.2014.2353672 10.1109/TEVC.2006.876362 10.1109/TEVC.2005.861417 10.1145/1527125.1527138 10.1007/s00500-015-1940-x 10.1109/TEVC.2015.2443001 10.1109/CEC.2007.4424987 10.1109/3468.650319 10.1109/CEC.2012.6256170 10.1109/TEVC.2010.2077298 10.1137/S1052623496307510 10.1109/4235.996017 10.1109/CEC.2016.7743898 10.1007/978-3-319-15892-1_8 10.1162/106365602760234108 10.1007/BF01584098 10.1016/j.knosys.2017.06.021 10.1145/1143997.1144113 10.1162/EVCO_a_00009 10.1016/0167-6377(86)90073-8 10.1109/ICEEE.2011.6106656 10.1109/TEVC.2010.2058117 10.1287/opre.45.5.751 10.1109/4235.797969 10.1109/TCYB.2014.2360923 10.1007/978-3-642-37140-0_24 10.1109/TEVC.2013.2258025 10.1007/978-3-540-70928-2_56 10.1109/TEVC.2014.2378512 10.1016/0377-2217(88)90257-3
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References	ref13 ref56 ref12 ref15 ref14 ref53 ref52 ref55 ref11 ref54 ref10 villalobos (ref37) 2012 szczepa?ski (ref51) 2003; 3 ref16 ref19 berenguer (ref63) 2015 ref18 emmerich (ref31) 2005 ref50 ref45 ref48 zitzler (ref5) 2002 ref47 ref42 ref41 ref44 ref43 steel (ref68) 1997 ref49 li (ref17) 2014; 18 ref8 ref7 ref9 ref4 deb (ref58) 1994; 9 ref6 ref40 ref35 deb (ref46) 2008 ref34 miller (ref57) 1995; 9 ref30 ref33 ref32 ref2 ref1 zou (ref25) 2008; 38 lygoe (ref3) 0 deb (ref59) 2001; 16 ref71 ref70 ishibuchi (ref39) 2015 trautmann (ref36) 0 lópez (ref27) 2013 ref24 ref67 ref23 ref26 storn (ref38) 1995; 3 ref64 ref20 ref66 ref22 ref65 ref21 deb (ref61) 1989 ref28 ref29 deb (ref69) 1996; 26 ref60 ref62
References_xml	– ident: ref53 doi: 10.1016/0167-188X(86)90030-3 – ident: ref7 doi: 10.1109/TEVC.2007.910138 – ident: ref44 doi: 10.1109/TEVC.2010.2093579 – start-page: 42 year: 1989 ident: ref61 article-title: An investigation of niche and species formation in genetic function optimization publication-title: Proc 3rd Int Conf Genet Algorithms – volume: 3 start-page: 16 year: 2003 ident: ref51 article-title: Application of multiple criteria evolutionary algorithms to vector optimisation, decision support and reference point approaches publication-title: J Telecommun Inf Technol – ident: ref48 doi: 10.1109/TEVC.2015.2455812 – volume: 18 start-page: 909 year: 2014 ident: ref17 article-title: Stable matching-based selection in evolutionary multiobjective optimization publication-title: IEEE Trans Evol Comput doi: 10.1109/TEVC.2013.2293776 – ident: ref23 doi: 10.1109/CISW.2007.4425478 – ident: ref33 doi: 10.1109/CEC.2007.4424730 – volume: 38 start-page: 1402 year: 2008 ident: ref25 article-title: A new evolutionary algorithm for solving many-objective optimization problems publication-title: IEEE Trans Syst Man Cybern B Cybern doi: 10.1109/TSMCB.2008.926329 – start-page: 62 year: 2005 ident: ref31 article-title: An EMO algorithm using the hypervolume measure as selection criterion publication-title: Proc Int Conf Evol Multi-Criterion Optim doi: 10.1007/978-3-540-31880-4_5 – ident: ref19 doi: 10.1109/TEVC.2014.2339823 – ident: ref32 doi: 10.1162/evco.2007.15.1.1 – ident: ref28 doi: 10.1109/TEVC.2013.2262178 – ident: ref8 doi: 10.1145/2792984 – ident: ref42 doi: 10.1109/CEC.2017.7969343 – ident: ref1 doi: 10.1007/3-540-36970-8_27 – start-page: 3 year: 2015 ident: ref63 article-title: Evolutionary many-objective optimization based on Kuhn-Munkres' algorithm publication-title: Proc Int Conf Evol Multi-Criterion Optim doi: 10.1007/978-3-319-15892-1_1 – ident: ref11 doi: 10.1109/TEVC.2015.2420112 – ident: ref41 doi: 10.1109/CEC.2016.7744269 – ident: ref29 doi: 10.1109/TEVC.2015.2424921 – ident: ref26 doi: 10.1109/TEVC.2012.2227145 – ident: ref64 doi: 10.1007/1-84628-137-7_6 – ident: ref18 doi: 10.1109/TCYB.2014.2365354 – start-page: 505 year: 2012 ident: ref37 article-title: A new multi-objective evolutionary algorithm based on a performance assessment indicator publication-title: Proc 14th Annu Conf Genetic Evol Comput – year: 1997 ident: ref68 publication-title: Principles and Procedures of Statistics A Biometrical Approach – ident: ref13 doi: 10.1109/TEVC.2016.2519378 – ident: ref14 doi: 10.1109/TEVC.2007.892759 – ident: ref16 doi: 10.1109/CEC.2014.6900319 – ident: ref47 doi: 10.1109/TSMCB.2012.2231860 – ident: ref71 doi: 10.1007/978-3-642-15871-1_10 – ident: ref10 doi: 10.1109/TEVC.2013.2281535 – ident: ref20 doi: 10.1109/TEVC.2014.2353672 – ident: ref22 doi: 10.1109/TEVC.2006.876362 – ident: ref65 doi: 10.1109/TEVC.2005.861417 – volume: 3 year: 1995 ident: ref38 publication-title: Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces – ident: ref70 doi: 10.1145/1527125.1527138 – ident: ref45 doi: 10.1007/s00500-015-1940-x – volume: 16 year: 2001 ident: ref59 publication-title: Multi-Objective Optimization Using Evolutionary Algorithms – ident: ref15 doi: 10.1109/TEVC.2015.2443001 – year: 2008 ident: ref46 article-title: A review of nadir point estimation procedures using evolutionary approaches: A tale of dimensionality reduction – ident: ref50 doi: 10.1109/CEC.2007.4424987 – start-page: 95 year: 2002 ident: ref5 article-title: SPEA2: Improving the strength Pareto evolutionary algorithm for multiobjective optimization publication-title: Proc Evol Methods Design Optim Control Appl Ind Problems (EUROGEN) – volume: 9 start-page: 1 year: 1994 ident: ref58 article-title: Simulated binary crossover for continuous search space publication-title: Complex Syst – ident: ref6 doi: 10.1109/3468.650319 – ident: ref2 doi: 10.1109/CEC.2012.6256170 – volume: 26 start-page: 30 year: 1996 ident: ref69 article-title: A combined genetic adaptive search (GeneAS) for engineering design publication-title: J Inform Comput Sci – ident: ref67 doi: 10.1109/TEVC.2010.2077298 – start-page: 89 year: 0 ident: ref36 article-title: Finding evenly spaced Pareto fronts for three-objective optimization problems publication-title: EVOLVE- A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation – ident: ref56 doi: 10.1137/S1052623496307510 – ident: ref4 doi: 10.1109/4235.996017 – ident: ref40 doi: 10.1109/CEC.2016.7743898 – start-page: 641 year: 0 ident: ref3 article-title: A real-world application of a many-objective optimisation complexity reduction process publication-title: Evolutionary Multi-Criterion Optimization – start-page: 110 year: 2015 ident: ref39 article-title: Modified distance calculation in generational distance and inverted generational distance publication-title: Proc Int Conf Evol Multi-Criterion Optim doi: 10.1007/978-3-319-15892-1_8 – ident: ref21 doi: 10.1162/106365602760234108 – ident: ref52 doi: 10.1007/BF01584098 – ident: ref12 doi: 10.1016/j.knosys.2017.06.021 – ident: ref43 doi: 10.1145/1143997.1144113 – ident: ref34 doi: 10.1162/EVCO_a_00009 – ident: ref62 doi: 10.1016/0167-6377(86)90073-8 – ident: ref35 doi: 10.1109/ICEEE.2011.6106656 – ident: ref60 doi: 10.1109/TEVC.2010.2058117 – ident: ref55 doi: 10.1287/opre.45.5.751 – ident: ref66 doi: 10.1109/4235.797969 – ident: ref49 doi: 10.1109/TCYB.2014.2360923 – start-page: 291 year: 2013 ident: ref27 article-title: An alternative preference relation to deal with many-objective optimization problems publication-title: Proc Int Conf Evol Multi-Criterion Optim doi: 10.1007/978-3-642-37140-0_24 – ident: ref24 doi: 10.1109/TEVC.2013.2258025 – volume: 9 start-page: 193 year: 1995 ident: ref57 article-title: Genetic algorithms, tournament selection, and the effects of noise publication-title: Complex Syst – ident: ref9 doi: 10.1007/978-3-540-70928-2_56 – ident: ref30 doi: 10.1109/TEVC.2014.2378512 – ident: ref54 doi: 10.1016/0377-2217(88)90257-3
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Snippet	Inverted generational distance (IGD) has been widely considered as a reliable performance indicator to concurrently quantify the convergence and diversity of...
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SubjectTerms	Algorithm design and analysis Approximation algorithms Business metrics Convergence Estimation Evolutionary algorithms Evolutionary computation Genetic algorithms Inverted generational distance (IGD) linear assignment problem (LAP) many-objective evolutionary optimization algorithm Multiple objective analysis nadir point Optimization Performance evaluation Performance measurement Sorting
Title	IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems
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