A new adaptive decomposition-based evolutionary algorithm for multi- and many-objective optimization
•An adaptive decomposition approach is proposed to guide the evolution process.•A structured metric is designed to assess the quality of the candidate solutions.•The structured metric performs differently on different rank fronts.•Once a weight vector is generated, the sub-objective space is divided...
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| Vydané v: | Expert systems with applications Ročník 213; s. 119080 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier Ltd
01.03.2023
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| ISSN: | 0957-4174, 1873-6793 |
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| Abstract | •An adaptive decomposition approach is proposed to guide the evolution process.•A structured metric is designed to assess the quality of the candidate solutions.•The structured metric performs differently on different rank fronts.•Once a weight vector is generated, the sub-objective space is divided into two ones.
In decomposition-based multi-objective evolutionary algorithms (MOEAs), a set of uniformly distributed reference vectors (RVs) is usually adopted to decompose a multi-objective optimization problem (MOP) into several single-objective sub-problems, and the RVs are fixed during evolution. When it comes to multi-objective optimization problems (MOPs) with complex Pareto fronts (PFs), the effectiveness of the multi-objective evolutionary algorithm (MOEA) may degrade. To solve this problem, this article proposes an adaptive decomposition-based evolutionary algorithm (ADEA) for both multi- and many-objective optimization. In ADEA, the candidate solutions themselves are used as RVs, so that the RVs can be automatically adjusted to the shape of the Pareto front (PF). Also, the RVs are successively generated one by one, and once a reference vector (RV) is generated, the corresponding sub-objective space is dynamically decomposed into two sub-spaces. Moreover, a variable metric is proposed and merged with the proposed adaptive decomposition approach to assist the selection operation in evolutionary many-objective optimization (EMO). The effectiveness of ADEA is compared with several state-of-the-art MOEAs on a variety of benchmark MOPs with up to 15 objectives. The empirical results demonstrate that ADEA has competitive performance on most of the MOPs used in this study. |
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| AbstractList | •An adaptive decomposition approach is proposed to guide the evolution process.•A structured metric is designed to assess the quality of the candidate solutions.•The structured metric performs differently on different rank fronts.•Once a weight vector is generated, the sub-objective space is divided into two ones.
In decomposition-based multi-objective evolutionary algorithms (MOEAs), a set of uniformly distributed reference vectors (RVs) is usually adopted to decompose a multi-objective optimization problem (MOP) into several single-objective sub-problems, and the RVs are fixed during evolution. When it comes to multi-objective optimization problems (MOPs) with complex Pareto fronts (PFs), the effectiveness of the multi-objective evolutionary algorithm (MOEA) may degrade. To solve this problem, this article proposes an adaptive decomposition-based evolutionary algorithm (ADEA) for both multi- and many-objective optimization. In ADEA, the candidate solutions themselves are used as RVs, so that the RVs can be automatically adjusted to the shape of the Pareto front (PF). Also, the RVs are successively generated one by one, and once a reference vector (RV) is generated, the corresponding sub-objective space is dynamically decomposed into two sub-spaces. Moreover, a variable metric is proposed and merged with the proposed adaptive decomposition approach to assist the selection operation in evolutionary many-objective optimization (EMO). The effectiveness of ADEA is compared with several state-of-the-art MOEAs on a variety of benchmark MOPs with up to 15 objectives. The empirical results demonstrate that ADEA has competitive performance on most of the MOPs used in this study. |
| ArticleNumber | 119080 |
| Author | Gao, Diju D.Goodman, Erik Gu, Wei Bao, Chunteng Xu, Lihong |
| Author_xml | – sequence: 1 givenname: Chunteng surname: Bao fullname: Bao, Chunteng email: jiuzhe321@163.com organization: Key Laboratory Marine Technology and Control Engineering, Ministry of Transport, Shanghai Maritime University, Shanghai, 201306, China – sequence: 2 givenname: Diju surname: Gao fullname: Gao, Diju email: djgao@shmtu.edu.cn organization: Key Laboratory Marine Technology and Control Engineering, Ministry of Transport, Shanghai Maritime University, Shanghai, 201306, China – sequence: 3 givenname: Wei surname: Gu fullname: Gu, Wei email: weigu@shmtu.edu.cn organization: Key Laboratory Marine Technology and Control Engineering, Ministry of Transport, Shanghai Maritime University, Shanghai, 201306, China – sequence: 4 givenname: Lihong surname: Xu fullname: Xu, Lihong email: xulhk@163.com organization: College of Electronics and Information Engineering, Tongji University, Shanghai, 201804, China – sequence: 5 givenname: Erik surname: D.Goodman fullname: D.Goodman, Erik email: goodman@egr.msu.edu organization: BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, MI 48824, USA |
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| Cites_doi | 10.1109/TEVC.2015.2420112 10.1109/TEVC.2015.2443001 10.1109/TCYB.2015.2507366 10.1109/TEVC.2013.2281534 10.1109/TEVC.2018.2883094 10.1162/106365600568202 10.1109/TEVC.2014.2378512 10.1109/TCYB.2017.2737519 10.1109/TEVC.2019.2915767 10.1109/TEVC.2016.2587808 10.1109/TEVC.2015.2455812 10.1109/ICNC.2011.6022367 10.1109/4235.797969 10.1109/TEVC.2018.2866854 10.1109/TEVC.2016.2519378 10.1016/j.swevo.2017.01.002 10.1016/j.ins.2020.06.028 10.1109/TCYB.2016.2638902 10.1109/TEVC.2016.2592479 10.1109/TEVC.2014.2308305 10.1109/TEVC.2013.2281535 10.1162/EVCO_a_00109 10.1109/TEVC.2013.2281533 10.1109/TEVC.2014.2373386 10.1109/TEVC.2010.2077298 10.1109/ACCESS.2017.2751071 10.1109/TEVC.2018.2848921 10.1109/TEVC.2007.892759 10.1109/TEVC.2020.3020046 10.1162/EVCO_a_00009 10.1109/TEVC.2017.2725902 10.1145/1527125.1527138 10.1109/TEVC.2020.2964705 10.1109/TEVC.2005.861417 10.1016/j.ins.2021.01.015 10.1137/S1052623496307510 10.1016/j.ejor.2006.08.008 10.1109/TEVC.2017.2749619 10.1109/TEVC.2015.2395073 10.1109/TEVC.2020.2991040 10.1109/TEVC.2016.2587749 10.1016/j.ins.2018.07.012 10.1109/TEVC.2020.3035825 10.1109/TEVC.2020.3016049 10.1109/TEVC.2017.2695579 10.1109/TEVC.2003.810758 10.1109/TEVC.2019.2909271 10.1109/4235.996017 10.1109/TCYB.2013.2247594 10.1007/978-3-319-45823-6_76 10.1109/TCYB.2017.2737554 |
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| Keywords | Pareto front Many-objective optimization Multi-objective evolutionary algorithm Adaptive decomposition |
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| References | Schott (b0155) 1995 Auger, A., Bader, J., Brockhoff, D., & Zitzler, E. (2009, January). Theory of the hypervolume indicator: optimal μ-distributions and the choice of the reference point. Deb, Jain (b0065) 2014; 18 Wang, Zhang, Li, Ishibuchi, Jiao (b0205) 2017; 34 Yuan, Xu, Wang, Yao (b0225) 2016; 20 Qi, Ma, Liu, Jiao, Sun, Wu (b0150) 2014; 22 Xiang, Zhou, Li, Chen (b0215) 2017; 21 Liu, Chen, Zhang, Deb (b0120) 2018; 22 Cheng, R., Li, M., Tian, Y., Zhang, X., Jin, Y., & Yao, X. (2017, June). Gu, Cheung (b0080) 2018; 22 Ma, Liu, Qi, Wang, Li, Jiao, Gong (b0135) 2016; 20 Beume, Naujoks, Emmerich (b0020) 2007; 181 Zhang, Tian, Cheng, Jin (b0250) 2015; 19 pp. 87-102 Wang, Yao (b0200) 2014; 44 Zhang, Li (b0245) 2007; 11 . Shanghai, China. Shang, Ishibuchi, Ni (b0165) 2020; 24 Cai, Xiao, Li, Hu, Ishibuchi, Li (b0030) 2021; 25 Jiang, S., Cai, Z., Zhang, J., & Ong, Y. S. (2011, July). Multiobjective optimization by decomposition with Pareto-adaptive weight vectors. https://doi.org/10.1145/1527125.1527138. Zhao, Zhang, Zhang (b0260) 2020; 540 Jiang, Yang (b0105) 2017; 21 Tomczyk, Kadziński (b0195) 2020; 24 San Francisco. Zhang, Tian, Jin (b0255) 2015; 19 Zitzler, Thiele (b0285) 1999; 3 Tanabe, Ishibuchi, Oyama (b0180) 2017; 5 Singh, Bhattacharjee, Ray (b0170) 2019; 23 Tian, Cheng, Zhang, Su, Jin (b0190) 2019; 23 Cheng, Jin, Narukawa, Sendhoff (b0035) 2015; 19 Jain, Deb (b0100) 2014; 18 Pamulapati, Mallipeddi, Suganthan (b0140) 2019; 23 Li, Deb, Zhang, Kwong (b0115) 2015; 19 While, Bradstreet, Barone (b0210) 2012; 16 Zitzler, Künzli (b0275) 2004, September Zitzler, Deb, Thiele (b0270) 2000; 8 Xu, Xue, Zhang (b0220) 2021; 25 Bader, Zitzler (b0015) 2011; 19 Asafuddoula, Singh, Ray (b0005) 2018; 48 Liu, Gong, Sun, Jin (b0130) 2017; 47 Edinburgh, United kingdom. https://doi.org/10.1007/978-3-319-45823-6_76. Tian, Cheng, Zhang, Cheng, Jin (b0185) 2018; 22 Zhang, Li, Li, Chen (b0240) 2021; 25 Liu, Gu, Zhang (b0125) 2014; 18 Das, Dennis (b0055) 1998; 8 Corne, D. W., Jerram, N. R., Knowles, J. D., & Oates, M. J. (2001, July). PESA-II: Region-based selection in evolutionary multiobjective optimization. Cai, Mei, Fan (b0025) 2018; 48 San Sebastián, Spain. Zhang, Wang, Li, Hu, Li, Wu (b0235) 2021; 563 Huband, Hingston, Barone, While (b0090) 2006; 10 H. Ishibuchi S. Yu H. Masuda Y. Nojima Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes IEEE Transactions on Evolutionary Computation 21 2 2017 169 190 https://doi.org/ 10.1109/TEVC.2016.2587749. Deb, Thiele, Laumanns, Zitzler (b0075) 2005 Li, Zhang, Deng (b0110) 2017; 47 Zitzler, Thiele, Laumanns, Fonseca, Da Fonseca (b0290) 2003; 7 Cheng, Jin, Olhofer, Sendhoff (b0040) 2016; 20 Picard, Schiffmann (b0145) 2021; 25 Shang, Ishibuchi (b0160) 2020; 24 Guerreiro, A. P., & Fonseca, C. M. (2016, September). Hypervolume sharpe-ratio indicator: Formalization and first theoretical results. Deb, Agrawal (b0060) 1995; 9 Deb, Pratap, Agarwal, Meyarivan (b0070) 2002; 6 Yuan, Xu, Wang, Zhang, Yao (b0230) 2016; 20 Zhou, Dai, Zhang, Li, Ma (b0265) 2018; 465 Jiang (10.1016/j.eswa.2022.119080_b0105) 2017; 21 Tanabe (10.1016/j.eswa.2022.119080_b0180) 2017; 5 Zitzler (10.1016/j.eswa.2022.119080_b0275) 2004 Ma (10.1016/j.eswa.2022.119080_b0135) 2016; 20 Zhang (10.1016/j.eswa.2022.119080_b0240) 2021; 25 Shang (10.1016/j.eswa.2022.119080_b0165) 2020; 24 Zhang (10.1016/j.eswa.2022.119080_b0250) 2015; 19 Xu (10.1016/j.eswa.2022.119080_b0220) 2021; 25 10.1016/j.eswa.2022.119080_b0010 Cai (10.1016/j.eswa.2022.119080_b0030) 2021; 25 10.1016/j.eswa.2022.119080_b0175 Singh (10.1016/j.eswa.2022.119080_b0170) 2019; 23 10.1016/j.eswa.2022.119080_b0095 10.1016/j.eswa.2022.119080_b0050 Tomczyk (10.1016/j.eswa.2022.119080_b0195) 2020; 24 Tian (10.1016/j.eswa.2022.119080_b0185) 2018; 22 Zitzler (10.1016/j.eswa.2022.119080_b0285) 1999; 3 Picard (10.1016/j.eswa.2022.119080_b0145) 2021; 25 Pamulapati (10.1016/j.eswa.2022.119080_b0140) 2019; 23 Gu (10.1016/j.eswa.2022.119080_b0080) 2018; 22 Tian (10.1016/j.eswa.2022.119080_b0190) 2019; 23 Zhang (10.1016/j.eswa.2022.119080_b0235) 2021; 563 Zitzler (10.1016/j.eswa.2022.119080_b0290) 2003; 7 Yuan (10.1016/j.eswa.2022.119080_b0230) 2016; 20 Zhao (10.1016/j.eswa.2022.119080_b0260) 2020; 540 Wang (10.1016/j.eswa.2022.119080_b0205) 2017; 34 Asafuddoula (10.1016/j.eswa.2022.119080_b0005) 2018; 48 Deb (10.1016/j.eswa.2022.119080_b0070) 2002; 6 Liu (10.1016/j.eswa.2022.119080_b0130) 2017; 47 Qi (10.1016/j.eswa.2022.119080_b0150) 2014; 22 Beume (10.1016/j.eswa.2022.119080_b0020) 2007; 181 Li (10.1016/j.eswa.2022.119080_b0115) 2015; 19 Zhou (10.1016/j.eswa.2022.119080_b0265) 2018; 465 Zitzler (10.1016/j.eswa.2022.119080_b0270) 2000; 8 Yuan (10.1016/j.eswa.2022.119080_b0225) 2016; 20 Cheng (10.1016/j.eswa.2022.119080_b0040) 2016; 20 Zhang (10.1016/j.eswa.2022.119080_b0255) 2015; 19 Liu (10.1016/j.eswa.2022.119080_b0125) 2014; 18 Huband (10.1016/j.eswa.2022.119080_b0090) 2006; 10 Xiang (10.1016/j.eswa.2022.119080_b0215) 2017; 21 Cheng (10.1016/j.eswa.2022.119080_b0035) 2015; 19 Cai (10.1016/j.eswa.2022.119080_b0025) 2018; 48 Deb (10.1016/j.eswa.2022.119080_b0075) 2005 Schott (10.1016/j.eswa.2022.119080_b0155) 1995 While (10.1016/j.eswa.2022.119080_b0210) 2012; 16 Jain (10.1016/j.eswa.2022.119080_b0100) 2014; 18 Wang (10.1016/j.eswa.2022.119080_b0200) 2014; 44 Shang (10.1016/j.eswa.2022.119080_b0160) 2020; 24 Liu (10.1016/j.eswa.2022.119080_b0120) 2018; 22 Li (10.1016/j.eswa.2022.119080_b0110) 2017; 47 10.1016/j.eswa.2022.119080_b0045 10.1016/j.eswa.2022.119080_b0085 Deb (10.1016/j.eswa.2022.119080_b0065) 2014; 18 Das (10.1016/j.eswa.2022.119080_b0055) 1998; 8 Bader (10.1016/j.eswa.2022.119080_b0015) 2011; 19 Zhang (10.1016/j.eswa.2022.119080_b0245) 2007; 11 Deb (10.1016/j.eswa.2022.119080_b0060) 1995; 9 |
| References_xml | – volume: 10 start-page: 477 year: 2006 end-page: 506 ident: b0090 article-title: A review of multiobjective test problems and a scalable test problem toolkit publication-title: IEEE Transactions on Evolutionary Computation – volume: 20 start-page: 16 year: 2016 end-page: 37 ident: b0225 article-title: A new dominance relation-based evolutionary algorithm for many-objective optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 16 start-page: 86 year: 2012 end-page: 95 ident: b0210 article-title: A fast way of calculating exact hypervolumes publication-title: IEEE Transactions on Evolutionary Computation – volume: 5 start-page: 19597 year: 2017 end-page: 19619 ident: b0180 article-title: Benchmarking Multi- and Many-Objective Evolutionary Algorithms Under Two Optimization Scenarios publication-title: IEEE Access – volume: 23 start-page: 331 year: 2019 end-page: 345 ident: b0190 article-title: A Strengthened Dominance Relation Considering Convergence and Diversity for Evolutionary Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 19 start-page: 761 year: 2015 end-page: 776 ident: b0255 article-title: A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 21 start-page: 329 year: 2017 end-page: 346 ident: b0105 article-title: A strength pareto evolutionary algorithm based on reference direction for multiobjective and many-objective optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 540 start-page: 435 year: 2020 end-page: 448 ident: b0260 article-title: A decomposition-based many-objective ant colony optimization algorithm with adaptive reference points publication-title: Information Sciences – volume: 9 start-page: 115 year: 1995 end-page: 148 ident: b0060 article-title: Simulated binary crossover for continuous search space publication-title: Complex Systems – volume: 47 start-page: 52 year: 2017 end-page: 66 ident: b0110 article-title: Biased Multiobjective Optimization and Decomposition Algorithm publication-title: IEEE Transactions on Cybernetics – volume: 19 start-page: 694 year: 2015 end-page: 716 ident: b0115 article-title: An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition publication-title: IEEE Transactions on Evolutionary Computation – volume: 34 start-page: 89 year: 2017 end-page: 102 ident: b0205 article-title: On the use of two reference points in decomposition based multiobjective evolutionary algorithms publication-title: Swarm and Evolutionary Computation – volume: 19 start-page: 45 year: 2011 end-page: 76 ident: b0015 article-title: HypE: An algorithm for fast hypervolume-based many-objective optimization publication-title: Evolutionary Computation – reference: , Edinburgh, United kingdom. https://doi.org/10.1007/978-3-319-45823-6_76. – reference: Cheng, R., Li, M., Tian, Y., Zhang, X., Jin, Y., & Yao, X. (2017, June). – reference: . San Sebastián, Spain. – volume: 465 start-page: 232 year: 2018 end-page: 247 ident: b0265 article-title: Entropy based evolutionary algorithm with adaptive reference points for many-objective optimization problems publication-title: Information Sciences – volume: 23 start-page: 904 year: 2019 end-page: 912 ident: b0170 article-title: Distance-Based Subset Selection for Benchmarking in Evolutionary Multi/Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 20 start-page: 180 year: 2016 end-page: 198 ident: b0230 article-title: Balancing Convergence and Diversity in Decomposition-Based Many-Objective Optimizers publication-title: IEEE Transactions on Evolutionary Computation – reference: Auger, A., Bader, J., Brockhoff, D., & Zitzler, E. (2009, January). Theory of the hypervolume indicator: optimal μ-distributions and the choice of the reference point. – volume: 22 start-page: 433 year: 2018 end-page: 448 ident: b0120 article-title: Adaptively Allocating Search Effort in Challenging Many-Objective Optimization Problems publication-title: IEEE Transactions on Evolutionary Computation – volume: 20 start-page: 773 year: 2016 end-page: 791 ident: b0040 article-title: A reference vector guided evolutionary algorithm for many-objective optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 48 start-page: 2321 year: 2018 end-page: 2334 ident: b0005 article-title: An enhanced decomposition-based evolutionary algorithm with adaptive reference vectors publication-title: IEEE Transactions on Cybernetics – volume: 47 start-page: 2689 year: 2017 end-page: 2702 ident: b0130 article-title: A Many-Objective Evolutionary Algorithm Using A One-by-One Selection Strategy publication-title: IEEE Transactions on Cybernetics – year: 1995 ident: b0155 article-title: Fault tolerant design using single and multicriteria genetic algorithm optimization – volume: 21 start-page: 131 year: 2017 end-page: 152 ident: b0215 article-title: A Vector Angle-Based Evolutionary Algorithm for Unconstrained Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 11 start-page: 712 year: 2007 end-page: 731 ident: b0245 article-title: MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition publication-title: IEEE Transactions on Evolutionary Computation – volume: 19 start-page: 201 year: 2015 end-page: 213 ident: b0250 article-title: An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 181 start-page: 1653 year: 2007 end-page: 1669 ident: b0020 article-title: SMS-EMOA: Multiobjective selection based on dominated hypervolume publication-title: European Journal of Operational Research – reference: https://doi.org/10.1145/1527125.1527138. – reference: Guerreiro, A. P., & Fonseca, C. M. (2016, September). Hypervolume sharpe-ratio indicator: Formalization and first theoretical results. – volume: 18 start-page: 450 year: 2014 end-page: 455 ident: b0125 article-title: Decomposition of a Multiobjective Optimization Problem Into a Number of Simple Multiobjective Subproblems publication-title: IEEE Transactions on Evolutionary Computation – volume: 3 start-page: 257 year: 1999 end-page: 271 ident: b0285 article-title: Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach publication-title: IEEE Transactions on Evolutionary Computation – volume: 24 start-page: 839 year: 2020 end-page: 852 ident: b0160 article-title: A New Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 563 start-page: 70 year: 2021 end-page: 90 ident: b0235 article-title: Many-Objective Evolutionary Algorithm with Adaptive Reference Vector publication-title: Information Sciences – volume: 24 start-page: 320 year: 2020 end-page: 334 ident: b0195 article-title: Decomposition-Based Interactive Evolutionary Algorithm for Multiple Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 48 start-page: 1 year: 2018 end-page: 14 ident: b0025 article-title: A Decomposition-Based Many-Objective Evolutionary Algorithm With Two Types of Adjustments for Direction Vectors publication-title: IEEE Transactions on Cybernetics – reference: (pp. 87-102) – volume: 25 start-page: 21 year: 2021 end-page: 34 ident: b0030 article-title: A Grid-Based Inverted Generational Distance for Multi/Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 8 start-page: 631 year: 1998 end-page: 657 ident: b0055 article-title: Normal-boundary intersection: A new method for generating the Pareto surface in nonlinear multicriteria optimization problems publication-title: SIAM Journal on Optimization – volume: 22 start-page: 609 year: 2018 end-page: 622 ident: b0185 article-title: An Indicator-Based Multiobjective Evolutionary Algorithm With Reference Point Adaptation for Better Versatility publication-title: IEEE Transactions on Evolutionary Computation – volume: 25 start-page: 205 year: 2021 end-page: 218 ident: b0220 article-title: A Duplication Analysis-Based Evolutionary Algorithm for Biobjective Feature Selection publication-title: IEEE Transactions on Evolutionary Computation – reference: Corne, D. W., Jerram, N. R., Knowles, J. D., & Oates, M. J. (2001, July). PESA-II: Region-based selection in evolutionary multiobjective optimization. – volume: 23 start-page: 346 year: 2019 end-page: 352 ident: b0140 article-title: —An Indicator for Multi and Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation – volume: 25 start-page: 234 year: 2021 end-page: 246 ident: b0145 article-title: Realistic Constrained Multiobjective Optimization Benchmark Problems From Design publication-title: IEEE Transactions on Evolutionary Computation – volume: 22 start-page: 211 year: 2018 end-page: 225 ident: b0080 article-title: Self-Organizing Map-Based Weight Design for Decomposition-Based Many-Objective Evolutionary Algorithm publication-title: IEEE Transactions on Evolutionary Computation – volume: 20 start-page: 275 year: 2016 end-page: 298 ident: b0135 article-title: A multiobjective evolutionary algorithm based on decision variable analyses for multiobjective optimization problems with large-scale variables publication-title: IEEE Transactions on Evolutionary Computation – volume: 44 start-page: 92 year: 2014 end-page: 102 ident: b0200 article-title: Corner Sort for Pareto-Based Many-Objective Optimization publication-title: IEEE Transactions on Cybernetics – volume: 18 start-page: 577 year: 2014 end-page: 601 ident: b0065 article-title: An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints publication-title: IEEE Transactions on Evolutionary Computation – start-page: 105 year: 2005 end-page: 145 ident: b0075 article-title: Scalable test problems for evolutionary multiobjective optimization publication-title: Evolutionary Multiobjective Optimization – reference: H. Ishibuchi S. Yu H. Masuda Y. Nojima Performance of Decomposition-Based Many-Objective Algorithms Strongly Depends on Pareto Front Shapes IEEE Transactions on Evolutionary Computation 21 2 2017 169 190 https://doi.org/ 10.1109/TEVC.2016.2587749. – volume: 7 start-page: 117 year: 2003 end-page: 132 ident: b0290 article-title: Performance assessment of multiobjective optimizers: An analysis and review publication-title: IEEE Transactions on Evolutionary Computation – volume: 6 start-page: 182 year: 2002 end-page: 197 ident: b0070 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Transactions on Evolutionary Computation – volume: 19 start-page: 838 year: 2015 end-page: 856 ident: b0035 article-title: A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modeling publication-title: IEEE Transactions on Evolutionary Computation – volume: 25 start-page: 334 year: 2021 end-page: 345 ident: b0240 article-title: A New Many-Objective Evolutionary Algorithm Based on Determinantal Point Processes publication-title: IEEE Transactions on Evolutionary Computation – volume: 8 start-page: 173 year: 2000 end-page: 195 ident: b0270 article-title: Comparison of Multiobjective Evolutionary Algorithms: Empirical Results publication-title: Evolutionary Computation – reference: . – volume: 22 start-page: 231 year: 2014 end-page: 264 ident: b0150 article-title: MOEA/D with adaptive weight adjustment publication-title: Evolutionary Computation – volume: 18 start-page: 602 year: 2014 end-page: 622 ident: b0100 article-title: An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point Based Nondominated Sorting Approach, Part II: Handling Constraints and Extending to an Adaptive Approach publication-title: IEEE Transactions on Evolutionary Computation – volume: 24 start-page: 185 year: 2020 end-page: 192 ident: b0165 article-title: R2-Based Hypervolume Contribution Approximation publication-title: IEEE Transactions on Evolutionary Computation – reference: , San Francisco. – start-page: 832 year: 2004, September end-page: 842 ident: b0275 article-title: Indicator-based selection in multiobjective search publication-title: International Conference on Parallel Problem Solving from Nature – reference: , Shanghai, China. – reference: Jiang, S., Cai, Z., Zhang, J., & Ong, Y. S. (2011, July). Multiobjective optimization by decomposition with Pareto-adaptive weight vectors. – volume: 20 start-page: 16 issue: 1 year: 2016 ident: 10.1016/j.eswa.2022.119080_b0225 article-title: A new dominance relation-based evolutionary algorithm for many-objective optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2015.2420112 – volume: 20 start-page: 180 issue: 2 year: 2016 ident: 10.1016/j.eswa.2022.119080_b0230 article-title: Balancing Convergence and Diversity in Decomposition-Based Many-Objective Optimizers publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2015.2443001 – volume: 9 start-page: 115 issue: 2 year: 1995 ident: 10.1016/j.eswa.2022.119080_b0060 article-title: Simulated binary crossover for continuous search space publication-title: Complex Systems – volume: 47 start-page: 52 issue: 1 year: 2017 ident: 10.1016/j.eswa.2022.119080_b0110 article-title: Biased Multiobjective Optimization and Decomposition Algorithm publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TCYB.2015.2507366 – volume: 18 start-page: 602 issue: 4 year: 2014 ident: 10.1016/j.eswa.2022.119080_b0100 article-title: An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point Based Nondominated Sorting Approach, Part II: Handling Constraints and Extending to an Adaptive Approach publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2013.2281534 – volume: 23 start-page: 904 issue: 5 year: 2019 ident: 10.1016/j.eswa.2022.119080_b0170 article-title: Distance-Based Subset Selection for Benchmarking in Evolutionary Multi/Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2018.2883094 – volume: 8 start-page: 173 issue: 2 year: 2000 ident: 10.1016/j.eswa.2022.119080_b0270 article-title: Comparison of Multiobjective Evolutionary Algorithms: Empirical Results publication-title: Evolutionary Computation doi: 10.1162/106365600568202 – volume: 19 start-page: 761 issue: 6 year: 2015 ident: 10.1016/j.eswa.2022.119080_b0255 article-title: A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2014.2378512 – volume: 48 start-page: 2321 issue: 8 year: 2018 ident: 10.1016/j.eswa.2022.119080_b0005 article-title: An enhanced decomposition-based evolutionary algorithm with adaptive reference vectors publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TCYB.2017.2737519 – volume: 24 start-page: 320 issue: 2 year: 2020 ident: 10.1016/j.eswa.2022.119080_b0195 article-title: Decomposition-Based Interactive Evolutionary Algorithm for Multiple Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2019.2915767 – volume: 21 start-page: 131 issue: 1 year: 2017 ident: 10.1016/j.eswa.2022.119080_b0215 article-title: A Vector Angle-Based Evolutionary Algorithm for Unconstrained Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2016.2587808 – volume: 20 start-page: 275 issue: 2 year: 2016 ident: 10.1016/j.eswa.2022.119080_b0135 article-title: A multiobjective evolutionary algorithm based on decision variable analyses for multiobjective optimization problems with large-scale variables publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2015.2455812 – ident: 10.1016/j.eswa.2022.119080_b0175 doi: 10.1109/ICNC.2011.6022367 – volume: 3 start-page: 257 issue: 4 year: 1999 ident: 10.1016/j.eswa.2022.119080_b0285 article-title: Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.797969 – volume: 23 start-page: 331 issue: 2 year: 2019 ident: 10.1016/j.eswa.2022.119080_b0190 article-title: A Strengthened Dominance Relation Considering Convergence and Diversity for Evolutionary Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2018.2866854 – volume: 20 start-page: 773 issue: 5 year: 2016 ident: 10.1016/j.eswa.2022.119080_b0040 article-title: A reference vector guided evolutionary algorithm for many-objective optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2016.2519378 – year: 1995 ident: 10.1016/j.eswa.2022.119080_b0155 – volume: 34 start-page: 89 year: 2017 ident: 10.1016/j.eswa.2022.119080_b0205 article-title: On the use of two reference points in decomposition based multiobjective evolutionary algorithms publication-title: Swarm and Evolutionary Computation doi: 10.1016/j.swevo.2017.01.002 – volume: 540 start-page: 435 year: 2020 ident: 10.1016/j.eswa.2022.119080_b0260 article-title: A decomposition-based many-objective ant colony optimization algorithm with adaptive reference points publication-title: Information Sciences doi: 10.1016/j.ins.2020.06.028 – volume: 47 start-page: 2689 issue: 9 year: 2017 ident: 10.1016/j.eswa.2022.119080_b0130 article-title: A Many-Objective Evolutionary Algorithm Using A One-by-One Selection Strategy publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TCYB.2016.2638902 – ident: 10.1016/j.eswa.2022.119080_b0045 – volume: 21 start-page: 329 issue: 3 year: 2017 ident: 10.1016/j.eswa.2022.119080_b0105 article-title: A strength pareto evolutionary algorithm based on reference direction for multiobjective and many-objective optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2016.2592479 – volume: 19 start-page: 201 issue: 2 year: 2015 ident: 10.1016/j.eswa.2022.119080_b0250 article-title: An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective Optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2014.2308305 – volume: 18 start-page: 577 issue: 4 year: 2014 ident: 10.1016/j.eswa.2022.119080_b0065 article-title: An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2013.2281535 – volume: 22 start-page: 231 issue: 2 year: 2014 ident: 10.1016/j.eswa.2022.119080_b0150 article-title: MOEA/D with adaptive weight adjustment publication-title: Evolutionary Computation doi: 10.1162/EVCO_a_00109 – volume: 18 start-page: 450 issue: 3 year: 2014 ident: 10.1016/j.eswa.2022.119080_b0125 article-title: Decomposition of a Multiobjective Optimization Problem Into a Number of Simple Multiobjective Subproblems publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2013.2281533 – start-page: 105 year: 2005 ident: 10.1016/j.eswa.2022.119080_b0075 article-title: Scalable test problems for evolutionary multiobjective optimization – volume: 19 start-page: 694 issue: 5 year: 2015 ident: 10.1016/j.eswa.2022.119080_b0115 article-title: An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2014.2373386 – volume: 16 start-page: 86 issue: 1 year: 2012 ident: 10.1016/j.eswa.2022.119080_b0210 article-title: A fast way of calculating exact hypervolumes publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2010.2077298 – volume: 5 start-page: 19597 year: 2017 ident: 10.1016/j.eswa.2022.119080_b0180 article-title: Benchmarking Multi- and Many-Objective Evolutionary Algorithms Under Two Optimization Scenarios publication-title: IEEE Access doi: 10.1109/ACCESS.2017.2751071 – volume: 23 start-page: 346 issue: 2 year: 2019 ident: 10.1016/j.eswa.2022.119080_b0140 article-title: ISDE+—An Indicator for Multi and Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2018.2848921 – volume: 11 start-page: 712 issue: 6 year: 2007 ident: 10.1016/j.eswa.2022.119080_b0245 article-title: MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2007.892759 – volume: 25 start-page: 234 issue: 2 year: 2021 ident: 10.1016/j.eswa.2022.119080_b0145 article-title: Realistic Constrained Multiobjective Optimization Benchmark Problems From Design publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2020.3020046 – volume: 19 start-page: 45 issue: 1 year: 2011 ident: 10.1016/j.eswa.2022.119080_b0015 article-title: HypE: An algorithm for fast hypervolume-based many-objective optimization publication-title: Evolutionary Computation doi: 10.1162/EVCO_a_00009 – volume: 22 start-page: 433 issue: 3 year: 2018 ident: 10.1016/j.eswa.2022.119080_b0120 article-title: Adaptively Allocating Search Effort in Challenging Many-Objective Optimization Problems publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2017.2725902 – ident: 10.1016/j.eswa.2022.119080_b0010 doi: 10.1145/1527125.1527138 – volume: 24 start-page: 839 issue: 5 year: 2020 ident: 10.1016/j.eswa.2022.119080_b0160 article-title: A New Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2020.2964705 – volume: 10 start-page: 477 issue: 5 year: 2006 ident: 10.1016/j.eswa.2022.119080_b0090 article-title: A review of multiobjective test problems and a scalable test problem toolkit publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2005.861417 – volume: 563 start-page: 70 year: 2021 ident: 10.1016/j.eswa.2022.119080_b0235 article-title: Many-Objective Evolutionary Algorithm with Adaptive Reference Vector publication-title: Information Sciences doi: 10.1016/j.ins.2021.01.015 – volume: 8 start-page: 631 issue: 3 year: 1998 ident: 10.1016/j.eswa.2022.119080_b0055 article-title: Normal-boundary intersection: A new method for generating the Pareto surface in nonlinear multicriteria optimization problems publication-title: SIAM Journal on Optimization doi: 10.1137/S1052623496307510 – volume: 181 start-page: 1653 issue: 3 year: 2007 ident: 10.1016/j.eswa.2022.119080_b0020 article-title: SMS-EMOA: Multiobjective selection based on dominated hypervolume publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2006.08.008 – start-page: 832 year: 2004 ident: 10.1016/j.eswa.2022.119080_b0275 article-title: Indicator-based selection in multiobjective search – volume: 22 start-page: 609 issue: 4 year: 2018 ident: 10.1016/j.eswa.2022.119080_b0185 article-title: An Indicator-Based Multiobjective Evolutionary Algorithm With Reference Point Adaptation for Better Versatility publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2017.2749619 – volume: 19 start-page: 838 issue: 6 year: 2015 ident: 10.1016/j.eswa.2022.119080_b0035 article-title: A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modeling publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2015.2395073 – ident: 10.1016/j.eswa.2022.119080_b0050 – volume: 25 start-page: 21 issue: 1 year: 2021 ident: 10.1016/j.eswa.2022.119080_b0030 article-title: A Grid-Based Inverted Generational Distance for Multi/Many-Objective Optimization publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2020.2991040 – ident: 10.1016/j.eswa.2022.119080_b0095 doi: 10.1109/TEVC.2016.2587749 – volume: 465 start-page: 232 year: 2018 ident: 10.1016/j.eswa.2022.119080_b0265 article-title: Entropy based evolutionary algorithm with adaptive reference points for many-objective optimization problems publication-title: Information Sciences doi: 10.1016/j.ins.2018.07.012 – volume: 25 start-page: 334 issue: 2 year: 2021 ident: 10.1016/j.eswa.2022.119080_b0240 article-title: A New Many-Objective Evolutionary Algorithm Based on Determinantal Point Processes publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2020.3035825 – volume: 25 start-page: 205 issue: 2 year: 2021 ident: 10.1016/j.eswa.2022.119080_b0220 article-title: A Duplication Analysis-Based Evolutionary Algorithm for Biobjective Feature Selection publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2020.3016049 – volume: 22 start-page: 211 issue: 2 year: 2018 ident: 10.1016/j.eswa.2022.119080_b0080 article-title: Self-Organizing Map-Based Weight Design for Decomposition-Based Many-Objective Evolutionary Algorithm publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2017.2695579 – volume: 7 start-page: 117 issue: 2 year: 2003 ident: 10.1016/j.eswa.2022.119080_b0290 article-title: Performance assessment of multiobjective optimizers: An analysis and review publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2003.810758 – volume: 24 start-page: 185 issue: 1 year: 2020 ident: 10.1016/j.eswa.2022.119080_b0165 article-title: R2-Based Hypervolume Contribution Approximation publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/TEVC.2019.2909271 – volume: 6 start-page: 182 issue: 2 year: 2002 ident: 10.1016/j.eswa.2022.119080_b0070 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Transactions on Evolutionary Computation doi: 10.1109/4235.996017 – volume: 44 start-page: 92 issue: 1 year: 2014 ident: 10.1016/j.eswa.2022.119080_b0200 article-title: Corner Sort for Pareto-Based Many-Objective Optimization publication-title: IEEE Transactions on Cybernetics doi: 10.1109/TCYB.2013.2247594 – ident: 10.1016/j.eswa.2022.119080_b0085 doi: 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| SubjectTerms | Adaptive decomposition Many-objective optimization Multi-objective evolutionary algorithm Pareto front |
| Title | A new adaptive decomposition-based evolutionary algorithm for multi- and many-objective optimization |
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