Walsh-based surrogate-assisted multi-objective combinatorial optimization: A fine-grained analysis for pseudo-boolean functions
The aim of this paper is to study surrogate-assisted algorithms for expensive multiobjective combinatorial optimization problems. Targeting pseudo-boolean domains, we provide a fine-grained analysis of an optimization framework using the Walsh basis as a core surrogate model. The considered framewor...
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| Vydáno v: | Applied soft computing Ročník 136; s. 110061 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier B.V
01.03.2023
Elsevier |
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| ISSN: | 1568-4946, 1872-9681 |
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| Abstract | The aim of this paper is to study surrogate-assisted algorithms for expensive multiobjective combinatorial optimization problems. Targeting pseudo-boolean domains, we provide a fine-grained analysis of an optimization framework using the Walsh basis as a core surrogate model. The considered framework uses decomposition in the objective space, and integrates three different components, namely, (i) an inner optimizer for searching promising solutions with respect to the so-constructed surrogate, (ii) a selection strategy to decide which solution is to be evaluated by the expensive objectives, and (iii) the strategy used to setup the Walsh order hyper-parameter. Based on extensive experiments using two benchmark problems, namely bi-objective NK-landscapes and unconstrained binary quadratic programming problems (UBQP), we conduct a comprehensive in-depth analysis of the combined effects of the considered components on search performance, and provide evidence on the effectiveness of the proposed search strategies. As a by-product, our work shed more light on the key challenges for designing a successful surrogate-assisted multi-objective combinatorial search process.
•A surrogate-assisted framework for multiobjective pseudo-boolean problems is studied.•Evolutionary techniques are combined with Walsh functions as discrete surrogates.•The impact of design components is analyzed on MNK-landscapes and UBQP.•Strong dependencies exist between the surrogate optimizer and the selection strategy.•The configuration of the Walsh surrogate order is highly impactful. |
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| AbstractList | The aim of this paper is to study surrogate-assisted algorithms for expensive multiobjective combinatorial optimization problems. Targeting pseudo-boolean domains, we provide a fine-grained analysis of an optimization framework using the Walsh basis as a core surrogate model. The considered framework uses decomposition in the objective space, and integrates three different components, namely, (i) an inner optimizer for searching promising solutions with respect to the so-constructed surrogate, (ii) a selection strategy to decide which solution is to be evaluated by the expensive objectives, and (iii) the strategy used to setup the Walsh order hyper-parameter. Based on extensive experiments using two benchmark problems, namely bi-objective NK-landscapes and unconstrained binary quadratic programming problems (UBQP), we conduct a comprehensive in-depth analysis of the combined effects of the considered components on search performance, and provide evidence on the effectiveness of the proposed search strategies. As a by-product, our work shed more light on the key challenges for designing a successful surrogate-assisted multi-objective combinatorial search process. The aim of this paper is to study surrogate-assisted algorithms for expensive multiobjective combinatorial optimization problems. Targeting pseudo-boolean domains, we provide a fine-grained analysis of an optimization framework using the Walsh basis as a core surrogate model. The considered framework uses decomposition in the objective space, and integrates three different components, namely, (i) an inner optimizer for searching promising solutions with respect to the so-constructed surrogate, (ii) a selection strategy to decide which solution is to be evaluated by the expensive objectives, and (iii) the strategy used to setup the Walsh order hyper-parameter. Based on extensive experiments using two benchmark problems, namely bi-objective NK-landscapes and unconstrained binary quadratic programming problems (UBQP), we conduct a comprehensive in-depth analysis of the combined effects of the considered components on search performance, and provide evidence on the effectiveness of the proposed search strategies. As a by-product, our work shed more light on the key challenges for designing a successful surrogate-assisted multi-objective combinatorial search process. •A surrogate-assisted framework for multiobjective pseudo-boolean problems is studied.•Evolutionary techniques are combined with Walsh functions as discrete surrogates.•The impact of design components is analyzed on MNK-landscapes and UBQP.•Strong dependencies exist between the surrogate optimizer and the selection strategy.•The configuration of the Walsh surrogate order is highly impactful. |
| ArticleNumber | 110061 |
| Author | Derbel, Bilel Zhang, Qingfu Verel, Sébastien Liefooghe, Arnaud Pruvost, Geoffrey |
| Author_xml | – sequence: 1 givenname: Bilel surname: Derbel fullname: Derbel, Bilel email: bilel.derbel@univ-lille.fr organization: Univ. Lille, CNRS, Inria, Centrale Lille, UMR 9189 CRIStAL, F-59000 Lille, France – sequence: 2 givenname: Geoffrey surname: Pruvost fullname: Pruvost, Geoffrey email: geoffrey.pruvost@univ-lille.fr organization: Univ. Lille, CNRS, Inria, Centrale Lille, UMR 9189 CRIStAL, F-59000 Lille, France – sequence: 3 givenname: Arnaud surname: Liefooghe fullname: Liefooghe, Arnaud email: arnaud.liefooghe@univ-lille.fr organization: Univ. Lille, CNRS, Inria, Centrale Lille, UMR 9189 CRIStAL, F-59000 Lille, France – sequence: 4 givenname: Sébastien surname: Verel fullname: Verel, Sébastien email: verel@univ-littoral.fr organization: Univ. Littoral Côte d’Opale, UR 4491, LISIC, F-62100 Calais, France – sequence: 5 givenname: Qingfu surname: Zhang fullname: Zhang, Qingfu email: qingfu.zhang@cityu.edu.hk organization: City University of Hong Kong, Kowloon Tong, Hong Kong |
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| Keywords | Discrete surrogates Multi-objective optimization Decomposition |
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| References | Deshwal, Belakaria, Doppa (b59) 2021 Leprêtre, Fonlupt, Verel, Marion (b52) 2020 Zhang, Li (b22) 2007; 11 Walsh (b67) 1923; 45 Aguirre, Tanaka (b74) 2007; 181 Li, Wang, Dong, Shen, Chen (b34) 2022; 242 Zaefferer, Stork, Friese, Fischbach, Naujoks, Bartz-Beielstein (b40) 2014 Bethke (b70) 1980 Negoescu, Frazier, Powell (b55) 2011; 23 Miettinen (b10) 1998; vol. 12 Jin, Wang, Chugh, Guo, Miettinen (b6) 2019; 23 Hakanen, Malmberg, Ojalehto, Eyvindson (b48) 2018 Breiman (b20) 2001; 45 Deshwal, Belakaria, Doppa, Fern (b65) 2020 Chugh, Sindhya, Hakanen, Miettinen (b2) 2019; 23 Sun, Duan, Mao (b45) 2022; 148 Zaefferer (b38) 2018 Leprêtre, Fonlupt, Verel, Marion (b62) 2019 Leprêtre, Verel, Fonlupt, Marion (b57) 2019 Swingler (b60) 2020; 28 Kauffman (b78) 1993 Tian, Yang, Zhang, Duan, Zhang (b51) 2019; 3 Zitzler, Künzli (b27) 2004 Deb, Hussein, Roy, Pulido (b7) 2019; 23 Liefooghe, Verel, Hao (b76) 2014; 16 Moraglio, Kattan (b39) 2011 Trivedi, Srinivasan, Sanyal, Ghosh (b21) 2017; 21 Pruvost, Derbel, Liefooghe, Verel, Zhang (b68) 2020 Tibshirani (b72) 1996; 58 Ehrgott (b11) 2005 Hutter, Hoos, Leyton-Brown (b66) 2011 Zapotecas Martinez, Coello Coello (b30) 2013 Ponweiser, Wagner, Biermann, Vincze (b33) 2008 Goodfellow, Bengio, Courville (b18) 2016 Jin (b5) 2011; 1 Baptista, Poloczek (b41) 2018 Zitzler, Thiele, Laumanns, Fonseca, Grunert da Fonseca (b79) 2003; 7 Rieser (b53) 2010 Bartz-Beielstein, Zaefferer (b3) 2017; 55 Dushatskiy, Alderliesten, Bosman (b63) 2021; 1 Krige (b14) 1951; 52 Berveglieri, Derbel, Liefooghe, Aguirre, Tanaka (b37) 2019 Drouet, Verel, Do (b47) 2020 Buhmann (b17) 2009; vol. 12 Deb, Pratap, Agarwal, Meyarivan (b23) 2002; 6 Hussein, Deb (b32) 2016 Coello Coello, Lamont, Van Veldhuizen (b13) 2007 Rasmussen (b15) 2003; vol. 3176 Deb, Jain (b24) 2014; 18 Dong, Li, Wang, Song, Yu (b36) 2021; 220 Dong, Wang, Song, Zhang, An (b42) 2020; 94 Drucker, Burges, Kaufman, Smola, Vapnik (b16) 1996 Deb (b12) 2001 Horn, Wagner, Biermann, Weihs, Bischl (b8) 2015 Zhang, Liu, Tsang, Virginas (b29) 2010; 14 Verel, Liefooghe, Jourdan, Dhaenens (b75) 2013; 227 Gu, Wang, Xiong, Jiang, Chen (b44) 2021; 8 Wang, Jin (b50) 2020; 50 Breiman, Friedman, Olshen, Stone (b19) 1984 Li, Zhang (b69) 2009; 13 Romero, Ibeas, Moura, Benavente, Alonso (b54) 2012; 54 Regis (b46) 2021 Han, Wang (b61) 2021; 13 Dushatskiy, Mendrik, Alderliesten, Bosman (b58) 2019 Kochenberger, Hao, Glover, Lewis, Lü, Wang, Wang (b77) 2014; 28 Vérel, Derbel, Liefooghe, Aguirre, Tanaka (b56) 2018; vol. 11102 Pan, He, Tian, Wang, Zhang, Jin (b35) 2019; 23 Hastie, Tibshirani, Wainwright (b71) 2015 Paquete, Stützle (b73) 2006; 169 Allmendinger, Emmerich, Hakanen, Jin, Rigoni (b9) 2017; 24 Jain, Deb (b25) 2014; 18 Chugh, Jin, Miettinen, Hakanen, Sindhya (b31) 2018; 22 Regis (b49) 2020 Hansen, Auger, Finck, Ros (b80) 2009 Unanue, Merino, Lozano (b64) 2021 T. Bartz-Beielstein, A survey of model-based methods for global optimization, in: International Conference on Bioinspired Optimization Methods and their Applications, BIOMA, 2016, pp. 1–18. Beume, Naujoks, Emmerich (b26) 2007; 181 Stork, Friese, Zaefferer, Bartz-Beielstein, Fischbach, Breiderhoff, Naujoks, Tusar (b1) 2020; vol. 833 Knowles (b28) 2006; 10 Gu, Wang, Li, Li (b43) 2021; 223 Horn (10.1016/j.asoc.2023.110061_b8) 2015 Coello Coello (10.1016/j.asoc.2023.110061_b13) 2007 Hakanen (10.1016/j.asoc.2023.110061_b48) 2018 Trivedi (10.1016/j.asoc.2023.110061_b21) 2017; 21 Hussein (10.1016/j.asoc.2023.110061_b32) 2016 Leprêtre (10.1016/j.asoc.2023.110061_b52) 2020 Kauffman (10.1016/j.asoc.2023.110061_b78) 1993 Dushatskiy (10.1016/j.asoc.2023.110061_b63) 2021; 1 Hutter (10.1016/j.asoc.2023.110061_b66) 2011 Regis (10.1016/j.asoc.2023.110061_b46) 2021 Liefooghe (10.1016/j.asoc.2023.110061_b76) 2014; 16 Jin (10.1016/j.asoc.2023.110061_b5) 2011; 1 Chugh (10.1016/j.asoc.2023.110061_b31) 2018; 22 Drouet (10.1016/j.asoc.2023.110061_b47) 2020 Li (10.1016/j.asoc.2023.110061_b34) 2022; 242 Zhang (10.1016/j.asoc.2023.110061_b29) 2010; 14 Zaefferer (10.1016/j.asoc.2023.110061_b40) 2014 Han (10.1016/j.asoc.2023.110061_b61) 2021; 13 Swingler (10.1016/j.asoc.2023.110061_b60) 2020; 28 Miettinen (10.1016/j.asoc.2023.110061_b10) 1998; vol. 12 Romero (10.1016/j.asoc.2023.110061_b54) 2012; 54 Sun (10.1016/j.asoc.2023.110061_b45) 2022; 148 Negoescu (10.1016/j.asoc.2023.110061_b55) 2011; 23 Unanue (10.1016/j.asoc.2023.110061_b64) 2021 Tian (10.1016/j.asoc.2023.110061_b51) 2019; 3 Zaefferer (10.1016/j.asoc.2023.110061_b38) 2018 Jain (10.1016/j.asoc.2023.110061_b25) 2014; 18 Chugh (10.1016/j.asoc.2023.110061_b2) 2019; 23 Leprêtre (10.1016/j.asoc.2023.110061_b62) 2019 Vérel (10.1016/j.asoc.2023.110061_b56) 2018; vol. 11102 Wang (10.1016/j.asoc.2023.110061_b50) 2020; 50 Aguirre (10.1016/j.asoc.2023.110061_b74) 2007; 181 Dong (10.1016/j.asoc.2023.110061_b42) 2020; 94 Deshwal (10.1016/j.asoc.2023.110061_b59) 2021 Drucker (10.1016/j.asoc.2023.110061_b16) 1996 Buhmann (10.1016/j.asoc.2023.110061_b17) 2009; vol. 12 Hansen (10.1016/j.asoc.2023.110061_b80) 2009 Pruvost (10.1016/j.asoc.2023.110061_b68) 2020 Zitzler (10.1016/j.asoc.2023.110061_b79) 2003; 7 Jin (10.1016/j.asoc.2023.110061_b6) 2019; 23 Allmendinger (10.1016/j.asoc.2023.110061_b9) 2017; 24 10.1016/j.asoc.2023.110061_b4 Dong (10.1016/j.asoc.2023.110061_b36) 2021; 220 Stork (10.1016/j.asoc.2023.110061_b1) 2020; vol. 833 Berveglieri (10.1016/j.asoc.2023.110061_b37) 2019 Pan (10.1016/j.asoc.2023.110061_b35) 2019; 23 Li (10.1016/j.asoc.2023.110061_b69) 2009; 13 Deshwal (10.1016/j.asoc.2023.110061_b65) 2020 Bartz-Beielstein (10.1016/j.asoc.2023.110061_b3) 2017; 55 Rieser (10.1016/j.asoc.2023.110061_b53) 2010 Deb (10.1016/j.asoc.2023.110061_b7) 2019; 23 Rasmussen (10.1016/j.asoc.2023.110061_b15) 2003; vol. 3176 Gu (10.1016/j.asoc.2023.110061_b43) 2021; 223 Leprêtre (10.1016/j.asoc.2023.110061_b57) 2019 Kochenberger (10.1016/j.asoc.2023.110061_b77) 2014; 28 Tibshirani (10.1016/j.asoc.2023.110061_b72) 1996; 58 Hastie (10.1016/j.asoc.2023.110061_b71) 2015 Deb (10.1016/j.asoc.2023.110061_b12) 2001 Goodfellow (10.1016/j.asoc.2023.110061_b18) 2016 Dushatskiy (10.1016/j.asoc.2023.110061_b58) 2019 Bethke (10.1016/j.asoc.2023.110061_b70) 1980 Zitzler (10.1016/j.asoc.2023.110061_b27) 2004 Paquete (10.1016/j.asoc.2023.110061_b73) 2006; 169 Deb (10.1016/j.asoc.2023.110061_b23) 2002; 6 Knowles (10.1016/j.asoc.2023.110061_b28) 2006; 10 Gu (10.1016/j.asoc.2023.110061_b44) 2021; 8 Breiman (10.1016/j.asoc.2023.110061_b19) 1984 Zapotecas Martinez (10.1016/j.asoc.2023.110061_b30) 2013 Breiman (10.1016/j.asoc.2023.110061_b20) 2001; 45 Verel (10.1016/j.asoc.2023.110061_b75) 2013; 227 Moraglio (10.1016/j.asoc.2023.110061_b39) 2011 Deb (10.1016/j.asoc.2023.110061_b24) 2014; 18 Walsh (10.1016/j.asoc.2023.110061_b67) 1923; 45 Ehrgott (10.1016/j.asoc.2023.110061_b11) 2005 Ponweiser (10.1016/j.asoc.2023.110061_b33) 2008 Beume (10.1016/j.asoc.2023.110061_b26) 2007; 181 Baptista (10.1016/j.asoc.2023.110061_b41) 2018 Zhang (10.1016/j.asoc.2023.110061_b22) 2007; 11 Regis (10.1016/j.asoc.2023.110061_b49) 2020 Krige (10.1016/j.asoc.2023.110061_b14) 1951; 52 |
| References_xml | – year: 1984 ident: b19 article-title: Classification and Regression Trees – volume: 1 start-page: 61 year: 2011 end-page: 70 ident: b5 article-title: Surrogate-assisted evolutionary computation: Recent advances and future challenges publication-title: Swarm Evol. Comput. – volume: 28 start-page: 58 year: 2014 end-page: 81 ident: b77 article-title: The unconstrained binary quadratic programming problem: A survey publication-title: J. Comb. Optim. – start-page: 42 year: 2020 end-page: 52 ident: b52 article-title: Combinatorial surrogate-assisted optimization for bus stops spacing problem publication-title: International Conference on Artificial Evolution (Evolution Artificielle) – volume: 50 start-page: 536 year: 2020 end-page: 549 ident: b50 article-title: A random forest-assisted evolutionary algorithm for data-driven constrained multiobjective combinatorial optimization of trauma systems publication-title: IEEE Trans. Cybern. – volume: 11 start-page: 712 year: 2007 end-page: 731 ident: b22 article-title: MOEA/D: A multiobjective evolutionary algorithm based on decomposition publication-title: IEEE Trans. Evol. Comput. – start-page: 1405 year: 2013 end-page: 1412 ident: b30 article-title: MOEA/D assisted by RBF networks for expensive multi-objective optimization problems publication-title: The Genetic and Evolutionary Computation Conference – start-page: 542 year: 2020 end-page: 550 ident: b68 article-title: Surrogate-assisted multi-objective combinatorial optimization based on decomposition and Walsh basis publication-title: The Genetic and Evolutionary Computation Conference – volume: vol. 12 year: 1998 ident: b10 publication-title: Nonlinear Multiobjective Optimization – volume: 6 start-page: 182 year: 2002 end-page: 197 ident: b23 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Trans. Evol. Comput. – volume: 22 start-page: 129 year: 2018 end-page: 142 ident: b31 article-title: A surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive many-objective optimization publication-title: IEEE Trans. Evol. Comput. – start-page: 832 year: 2004 end-page: 842 ident: b27 article-title: Indicator-based selection in multiobjective search publication-title: Parallel Problem Solving from Nature - PPSN VIII – volume: 28 start-page: 317 year: 2020 end-page: 338 ident: b60 article-title: Learning and searching pseudo-boolean surrogate functions from small samples publication-title: Evol. Comput. – volume: 169 start-page: 943 year: 2006 end-page: 959 ident: b73 article-title: A study of stochastic local search algorithms for the biobjective QAP with correlated flow matrices publication-title: European J. Oper. Res. – volume: 23 start-page: 442 year: 2019 end-page: 458 ident: b6 article-title: Data-driven evolutionary optimization: An overview and case studies publication-title: IEEE Trans. Evol. Comput. – start-page: 42 year: 2019 end-page: 52 ident: b62 article-title: Combinatorial surrogate-assisted optimization for bus stops spacing problem publication-title: International Conference on Artificial Evolution (Evolution Artificielle) – volume: 18 start-page: 577 year: 2014 end-page: 601 ident: b24 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 Trans. Evol. Comput. – year: 1993 ident: b78 article-title: The Origins of Order – start-page: 155 year: 1996 end-page: 161 ident: b16 article-title: Support vector regression machines publication-title: Advances in Neural Information Processing Systems – volume: 23 start-page: 104 year: 2019 end-page: 116 ident: b7 article-title: A taxonomy for metamodeling frameworks for evolutionary multiobjective optimization publication-title: IEEE Trans. Evol. Comput. – volume: 16 start-page: 10 year: 2014 end-page: 19 ident: b76 article-title: A hybrid metaheuristic for multiobjective unconstrained binary quadratic programming publication-title: Appl. Soft Comput. – volume: 55 start-page: 154 year: 2017 end-page: 167 ident: b3 article-title: Model-based methods for continuous and discrete global optimization publication-title: Appl. Soft Comput. – year: 2016 ident: b18 publication-title: Deep Learning – volume: 23 start-page: 346 year: 2011 end-page: 363 ident: b55 article-title: The knowledge-gradient algorithm for sequencing experiments in drug discovery publication-title: INFORMS J. Comput. – volume: 45 start-page: 5 year: 1923 ident: b67 article-title: A closed set of normal orthogonal functions publication-title: Amer. J. Math. – volume: 148 year: 2022 ident: b45 article-title: A multi-objective adaptive surrogate modelling-based optimization algorithm for constrained hybrid problems publication-title: Environ. Model. Softw. – start-page: 2632 year: 2021 end-page: 2643 ident: b59 article-title: Bayesian optimization over hybrid spaces publication-title: International Conference on Machine Learning – year: 1980 ident: b70 article-title: Genetic Algorithms as Function Optimizers – volume: 24 start-page: 5 year: 2017 end-page: 24 ident: b9 article-title: Surrogate-assisted multicriteria optimization: Complexities, prospective solutions, and business case publication-title: J. Multi-Criteria Decis. Anal. – start-page: 64 year: 2015 end-page: 78 ident: b8 article-title: Model-based multi-objective optimization: Taxonomy, multi-point proposal, toolbox and benchmark publication-title: Evolutionary Multi-Criterion Optimization – volume: vol. 11102 start-page: 181 year: 2018 end-page: 193 ident: b56 article-title: A surrogate model based on walsh decomposition for Pseudo-Boolean functions publication-title: Parallel Problem Solving from Nature – PPSN XV – start-page: 203 year: 2020 end-page: 214 ident: b49 article-title: High-dimensional constrained discrete multi-objective optimization using surrogates publication-title: International Conference on Machine Learning, Optimization, and Data Science – volume: 7 start-page: 117 year: 2003 end-page: 132 ident: b79 article-title: Performance assessment of multiobjective optimizers: An analysis and review publication-title: IEEE Trans. Evol. Comput. – start-page: 753 year: 2019 end-page: 761 ident: b58 article-title: Convolutional neural network surrogate-assisted GOMEA publication-title: The Genetic and Evolutionary Computation Conference – volume: 227 start-page: 331 year: 2013 end-page: 342 ident: b75 article-title: On the structure of multiobjective combinatorial search space: MNK-landscapes with correlated objectives publication-title: European J. Oper. Res. – start-page: 871 year: 2014 end-page: 878 ident: b40 article-title: Efficient global optimization for combinatorial problems publication-title: The Genetic and Evolutionary Computation Conference – volume: 94 year: 2020 ident: b42 article-title: Kriging-assisted discrete global optimization (KDGO) for black-box problems with costly objective and constraints publication-title: Appl. Soft Comput. – volume: 58 start-page: 267 year: 1996 end-page: 288 ident: b72 article-title: Regression shrinkage and selection via the lasso publication-title: J. R. Stat. Soc. Ser. B Stat. Methodol. – start-page: 142 year: 2011 end-page: 154 ident: b39 article-title: Geometric generalisation of surrogate model based optimisation to combinatorial spaces publication-title: Evolutionary Computation in Combinatorial Optimization – start-page: 303 year: 2019 end-page: 311 ident: b57 article-title: Walsh functions as surrogate model for Pseudo-Boolean optimization problems publication-title: The Genetic and Evolutionary Computation Conference – year: 2007 ident: b13 article-title: Evolutionary Algorithms for Solving Multi-Objective Problems – volume: 23 start-page: 74 year: 2019 end-page: 88 ident: b35 article-title: A classification-based surrogate-assisted evolutionary algorithm for expensive many-objective optimization publication-title: IEEE Trans. Evol. Comput. – start-page: 391 year: 2021 end-page: 398 ident: b64 article-title: A general framework based on Walsh decomposition for combinatorial optimization problems publication-title: Congress on Evolutionary Computation – volume: 181 start-page: 1653 year: 2007 end-page: 1669 ident: b26 article-title: SMS-EMOA: Multiobjective selection based on dominated hypervolume publication-title: European J. Oper. Res. – volume: 220 year: 2021 ident: b36 article-title: Surrogate-guided multi-objective optimization (SGMOO) using an efficient online sampling strategy publication-title: Knowl.-Based Syst. – volume: 8 start-page: 2699 year: 2021 end-page: 2718 ident: b44 article-title: Surrogate-assisted evolutionary algorithm for expensive constrained multi-objective discrete optimization problems publication-title: Complex Intell. Syst. – reference: T. Bartz-Beielstein, A survey of model-based methods for global optimization, in: International Conference on Bioinspired Optimization Methods and their Applications, BIOMA, 2016, pp. 1–18. – start-page: 1870 year: 2021 end-page: 1878 ident: b46 article-title: A two-phase surrogate approach for high-dimensional constrained discrete multi-objective optimization publication-title: The Genetic and Evolutionary Computation Conference, GECCO Companion Volume – volume: 14 start-page: 456 year: 2010 end-page: 474 ident: b29 article-title: Expensive multiobjective optimization by MOEA/D with Gaussian process model publication-title: IEEE Trans. Evol. Comput. – volume: vol. 833 start-page: 225 year: 2020 end-page: 244 ident: b1 article-title: Open issues in surrogate-assisted optimization publication-title: High-Performance Simulation-Based Optimization – year: 2010 ident: b53 article-title: Adding Transit to an Agent-Based Transportation Simulation: Concepts and Implementation – volume: 21 start-page: 440 year: 2017 end-page: 462 ident: b21 article-title: A survey of multiobjective evolutionary algorithms based on decomposition publication-title: IEEE Trans. Evol. Comput. – start-page: 784 year: 2008 end-page: 794 ident: b33 article-title: Multiobjective optimization on a limited budget of evaluations using model-assisted S-metric selection publication-title: Parallel Problem Solving from Nature – PPSN X – start-page: 3773 year: 2020 end-page: 3780 ident: b65 article-title: Optimizing discrete spaces via expensive evaluations: A learning to search framework publication-title: The AAAI Conference on Artificial Intelligence – volume: 223 year: 2021 ident: b43 article-title: A surrogate-assisted multi-objective particle swarm optimization of expensive constrained combinatorial optimization problems publication-title: Knowl.-Based Syst. – start-page: 507 year: 2011 end-page: 523 ident: b66 article-title: Sequential model-based optimization for general algorithm configuration publication-title: Learning and Intelligent Optimization – volume: 54 start-page: 646 year: 2012 end-page: 655 ident: b54 article-title: A simulation-optimization approach to design efficient systems of bike-sharing publication-title: Procedia Soc. Behav. Sci. – start-page: 507 year: 2019 end-page: -515 ident: b37 article-title: Surrogate-assisted multiobjective optimization based on decomposition: A comprehensive comparative analysis publication-title: The Genetic and Evolutionary Computation Conference – start-page: 104 year: 2018 end-page: 115 ident: b48 article-title: Data-driven interactive multiobjective optimization using a cluster-based surrogate in a discrete decision space publication-title: International Conference on Machine Learning, Optimization, and Data Science – volume: 3 start-page: 106 year: 2019 end-page: 116 ident: b51 article-title: A surrogate-assisted multiobjective evolutionary algorithm for large-scale task-oriented pattern mining publication-title: IEEE Trans. Emerg. Top. Comput. Intell. – volume: 45 start-page: 5 year: 2001 end-page: 32 ident: b20 article-title: Random forests publication-title: Mach. Learn. – start-page: 1073 year: 2020 end-page: 1081 ident: b47 article-title: Surrogate-assisted asynchronous multiobjective algorithm for nuclear power plant operations publication-title: The Genetic and Evolutionary Computation Conference – year: 2005 ident: b11 article-title: Multicriteria Optimization – volume: 52 start-page: 119 year: 1951 end-page: 139 ident: b14 article-title: A statistical approach to some basic mine valuation problems on the Witwatersrand publication-title: J. South. Afr. Inst. Min. Metall. – year: 2009 ident: b80 article-title: Real-Parameter Black-Box Optimization Benchmarking 2009: Experimental Setup – year: 2015 ident: b71 article-title: Statistical Learning with Sparsity: The Lasso and Generalizations – year: 2018 ident: b41 article-title: Bayesian optimization of combinatorial structures publication-title: ICML – volume: 13 start-page: 19 year: 2021 end-page: 30 ident: b61 article-title: A random forest assisted evolutionary algorithm using competitive neighborhood search for expensive constrained combinatorial optimization publication-title: Memetic Comput. – volume: 23 start-page: 3137 year: 2019 end-page: 3166 ident: b2 article-title: A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms publication-title: Soft Comput. – volume: 13 start-page: 284 year: 2009 end-page: 302 ident: b69 article-title: Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II publication-title: IEEE Trans. Evol. Comput. – volume: 18 start-page: 602 year: 2014 end-page: 622 ident: b25 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 Trans. Evol. Comput. – volume: 10 start-page: 50 year: 2006 end-page: 66 ident: b28 article-title: ParEGO: A hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems publication-title: IEEE Trans. Evol. Comput. – volume: 1 start-page: 1 year: 2021 end-page: 23 ident: b63 article-title: A novel approach to designing surrogate-assisted genetic algorithms by combining efficient learning of Walsh coefficients and dependencies publication-title: ACM Trans. Evol. Learn. Optim. – volume: 242 year: 2022 ident: b34 article-title: A classification surrogate-assisted multi-objective evolutionary algorithm for expensive optimization publication-title: Knowl.-Based Syst. – volume: vol. 12 year: 2009 ident: b17 publication-title: Radial Basis Functions - Theory and Implementations – year: 2018 ident: b38 article-title: Surrogate Models for Discrete Optimization Problems – volume: 181 start-page: 1670 year: 2007 end-page: 1690 ident: b74 article-title: Working principles, behavior, and performance of MOEAs on MNK-landscapes publication-title: European J. Oper. Res. – volume: vol. 3176 start-page: 63 year: 2003 end-page: 71 ident: b15 article-title: Gaussian processes in machine learning publication-title: Advanced Lectures on Machine Learning, ML Summer Schools, Canberra, Australia, February 2–14, Tübingen, Germany, August 4–16, Revised Lectures – start-page: 573 year: 2016 end-page: 580 ident: b32 article-title: A generative kriging surrogate model for constrained and unconstrained multi-objective optimization publication-title: The Genetic and Evolutionary Computation Conference – year: 2001 ident: b12 article-title: Multi-Objective Optimization using Evolutionary Algorithms – start-page: 64 year: 2015 ident: 10.1016/j.asoc.2023.110061_b8 article-title: Model-based multi-objective optimization: Taxonomy, multi-point proposal, toolbox and benchmark – start-page: 542 year: 2020 ident: 10.1016/j.asoc.2023.110061_b68 article-title: Surrogate-assisted multi-objective combinatorial optimization based on decomposition and Walsh basis – start-page: 1870 year: 2021 ident: 10.1016/j.asoc.2023.110061_b46 article-title: A two-phase surrogate approach for high-dimensional constrained discrete multi-objective optimization – volume: 181 start-page: 1653 issue: 3 year: 2007 ident: 10.1016/j.asoc.2023.110061_b26 article-title: SMS-EMOA: Multiobjective selection based on dominated hypervolume publication-title: European J. Oper. Res. doi: 10.1016/j.ejor.2006.08.008 – volume: 10 start-page: 50 issue: 1 year: 2006 ident: 10.1016/j.asoc.2023.110061_b28 article-title: ParEGO: A hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2005.851274 – start-page: 753 year: 2019 ident: 10.1016/j.asoc.2023.110061_b58 article-title: Convolutional neural network surrogate-assisted GOMEA – volume: 223 year: 2021 ident: 10.1016/j.asoc.2023.110061_b43 article-title: A surrogate-assisted multi-objective particle swarm optimization of expensive constrained combinatorial optimization problems publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2021.107049 – volume: 13 start-page: 284 issue: 2 year: 2009 ident: 10.1016/j.asoc.2023.110061_b69 article-title: Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2008.925798 – volume: 14 start-page: 456 issue: 3 year: 2010 ident: 10.1016/j.asoc.2023.110061_b29 article-title: Expensive multiobjective optimization by MOEA/D with Gaussian process model publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2009.2033671 – volume: vol. 3176 start-page: 63 year: 2003 ident: 10.1016/j.asoc.2023.110061_b15 article-title: Gaussian processes in machine learning – volume: 3 start-page: 106 issue: 2 year: 2019 ident: 10.1016/j.asoc.2023.110061_b51 article-title: A surrogate-assisted multiobjective evolutionary algorithm for large-scale task-oriented pattern mining publication-title: IEEE Trans. Emerg. Top. Comput. Intell. doi: 10.1109/TETCI.2018.2872055 – volume: 54 start-page: 646 year: 2012 ident: 10.1016/j.asoc.2023.110061_b54 article-title: A simulation-optimization approach to design efficient systems of bike-sharing publication-title: Procedia Soc. Behav. Sci. doi: 10.1016/j.sbspro.2012.09.782 – start-page: 507 year: 2011 ident: 10.1016/j.asoc.2023.110061_b66 article-title: Sequential model-based optimization for general algorithm configuration – start-page: 1405 year: 2013 ident: 10.1016/j.asoc.2023.110061_b30 article-title: MOEA/D assisted by RBF networks for expensive multi-objective optimization problems – start-page: 155 year: 1996 ident: 10.1016/j.asoc.2023.110061_b16 article-title: Support vector regression machines – start-page: 2632 year: 2021 ident: 10.1016/j.asoc.2023.110061_b59 article-title: Bayesian optimization over hybrid spaces – year: 2009 ident: 10.1016/j.asoc.2023.110061_b80 – volume: 220 year: 2021 ident: 10.1016/j.asoc.2023.110061_b36 article-title: Surrogate-guided multi-objective optimization (SGMOO) using an efficient online sampling strategy publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2021.106919 – year: 2001 ident: 10.1016/j.asoc.2023.110061_b12 – volume: 55 start-page: 154 year: 2017 ident: 10.1016/j.asoc.2023.110061_b3 article-title: Model-based methods for continuous and discrete global optimization publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2017.01.039 – volume: vol. 12 year: 2009 ident: 10.1016/j.asoc.2023.110061_b17 – volume: 6 start-page: 182 issue: 2 year: 2002 ident: 10.1016/j.asoc.2023.110061_b23 article-title: A fast and elitist multiobjective genetic algorithm: NSGA-II publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.996017 – year: 1980 ident: 10.1016/j.asoc.2023.110061_b70 – year: 2010 ident: 10.1016/j.asoc.2023.110061_b53 – volume: 23 start-page: 3137 issue: 9 year: 2019 ident: 10.1016/j.asoc.2023.110061_b2 article-title: A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms publication-title: Soft Comput. doi: 10.1007/s00500-017-2965-0 – volume: 148 year: 2022 ident: 10.1016/j.asoc.2023.110061_b45 article-title: A multi-objective adaptive surrogate modelling-based optimization algorithm for constrained hybrid problems publication-title: Environ. Model. Softw. doi: 10.1016/j.envsoft.2021.105272 – start-page: 203 year: 2020 ident: 10.1016/j.asoc.2023.110061_b49 article-title: High-dimensional constrained discrete multi-objective optimization using surrogates – volume: 1 start-page: 61 issue: 2 year: 2011 ident: 10.1016/j.asoc.2023.110061_b5 article-title: Surrogate-assisted evolutionary computation: Recent advances and future challenges publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2011.05.001 – volume: 94 year: 2020 ident: 10.1016/j.asoc.2023.110061_b42 article-title: Kriging-assisted discrete global optimization (KDGO) for black-box problems with costly objective and constraints publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.106429 – volume: 28 start-page: 317 issue: 2 year: 2020 ident: 10.1016/j.asoc.2023.110061_b60 article-title: Learning and searching pseudo-boolean surrogate functions from small samples publication-title: Evol. Comput. doi: 10.1162/evco_a_00257 – volume: 23 start-page: 74 issue: 1 year: 2019 ident: 10.1016/j.asoc.2023.110061_b35 article-title: A classification-based surrogate-assisted evolutionary algorithm for expensive many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2018.2802784 – volume: vol. 11102 start-page: 181 year: 2018 ident: 10.1016/j.asoc.2023.110061_b56 article-title: A surrogate model based on walsh decomposition for Pseudo-Boolean functions – year: 2005 ident: 10.1016/j.asoc.2023.110061_b11 – volume: 52 start-page: 119 issue: 6 year: 1951 ident: 10.1016/j.asoc.2023.110061_b14 article-title: A statistical approach to some basic mine valuation problems on the Witwatersrand publication-title: J. South. Afr. Inst. Min. Metall. – start-page: 104 year: 2018 ident: 10.1016/j.asoc.2023.110061_b48 article-title: Data-driven interactive multiobjective optimization using a cluster-based surrogate in a discrete decision space – start-page: 871 year: 2014 ident: 10.1016/j.asoc.2023.110061_b40 article-title: Efficient global optimization for combinatorial problems – start-page: 832 year: 2004 ident: 10.1016/j.asoc.2023.110061_b27 article-title: Indicator-based selection in multiobjective search – volume: 23 start-page: 346 issue: 3 year: 2011 ident: 10.1016/j.asoc.2023.110061_b55 article-title: The knowledge-gradient algorithm for sequencing experiments in drug discovery publication-title: INFORMS J. Comput. doi: 10.1287/ijoc.1100.0417 – year: 2016 ident: 10.1016/j.asoc.2023.110061_b18 – year: 1993 ident: 10.1016/j.asoc.2023.110061_b78 – start-page: 1073 year: 2020 ident: 10.1016/j.asoc.2023.110061_b47 article-title: Surrogate-assisted asynchronous multiobjective algorithm for nuclear power plant operations – year: 1984 ident: 10.1016/j.asoc.2023.110061_b19 – volume: 23 start-page: 104 issue: 1 year: 2019 ident: 10.1016/j.asoc.2023.110061_b7 article-title: A taxonomy for metamodeling frameworks for evolutionary multiobjective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2018.2828091 – start-page: 391 year: 2021 ident: 10.1016/j.asoc.2023.110061_b64 article-title: A general framework based on Walsh decomposition for combinatorial optimization problems – year: 2015 ident: 10.1016/j.asoc.2023.110061_b71 – start-page: 142 year: 2011 ident: 10.1016/j.asoc.2023.110061_b39 article-title: Geometric generalisation of surrogate model based optimisation to combinatorial spaces – year: 2007 ident: 10.1016/j.asoc.2023.110061_b13 – volume: 18 start-page: 602 issue: 4 year: 2014 ident: 10.1016/j.asoc.2023.110061_b25 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 Trans. Evol. Comput. doi: 10.1109/TEVC.2013.2281534 – ident: 10.1016/j.asoc.2023.110061_b4 – volume: 13 start-page: 19 year: 2021 ident: 10.1016/j.asoc.2023.110061_b61 article-title: A random forest assisted evolutionary algorithm using competitive neighborhood search for expensive constrained combinatorial optimization publication-title: Memetic Comput. doi: 10.1007/s12293-021-00326-9 – volume: vol. 833 start-page: 225 year: 2020 ident: 10.1016/j.asoc.2023.110061_b1 article-title: Open issues in surrogate-assisted optimization – start-page: 42 year: 2020 ident: 10.1016/j.asoc.2023.110061_b52 article-title: Combinatorial surrogate-assisted optimization for bus stops spacing problem – volume: 7 start-page: 117 issue: 2 year: 2003 ident: 10.1016/j.asoc.2023.110061_b79 article-title: Performance assessment of multiobjective optimizers: An analysis and review publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2003.810758 – start-page: 507 year: 2019 ident: 10.1016/j.asoc.2023.110061_b37 article-title: Surrogate-assisted multiobjective optimization based on decomposition: A comprehensive comparative analysis – volume: 22 start-page: 129 issue: 1 year: 2018 ident: 10.1016/j.asoc.2023.110061_b31 article-title: A surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive many-objective optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2016.2622301 – volume: 58 start-page: 267 issue: 1 year: 1996 ident: 10.1016/j.asoc.2023.110061_b72 article-title: Regression shrinkage and selection via the lasso publication-title: J. R. Stat. Soc. Ser. B Stat. Methodol. doi: 10.1111/j.2517-6161.1996.tb02080.x – volume: 169 start-page: 943 issue: 3 year: 2006 ident: 10.1016/j.asoc.2023.110061_b73 article-title: A study of stochastic local search algorithms for the biobjective QAP with correlated flow matrices publication-title: European J. Oper. Res. doi: 10.1016/j.ejor.2004.08.024 – volume: 16 start-page: 10 year: 2014 ident: 10.1016/j.asoc.2023.110061_b76 article-title: A hybrid metaheuristic for multiobjective unconstrained binary quadratic programming publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2013.11.008 – year: 2018 ident: 10.1016/j.asoc.2023.110061_b41 article-title: Bayesian optimization of combinatorial structures – volume: 23 start-page: 442 issue: 3 year: 2019 ident: 10.1016/j.asoc.2023.110061_b6 article-title: Data-driven evolutionary optimization: An overview and case studies publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2018.2869001 – volume: 18 start-page: 577 issue: 4 year: 2014 ident: 10.1016/j.asoc.2023.110061_b24 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 Trans. Evol. Comput. doi: 10.1109/TEVC.2013.2281535 – start-page: 784 year: 2008 ident: 10.1016/j.asoc.2023.110061_b33 article-title: Multiobjective optimization on a limited budget of evaluations using model-assisted S-metric selection – volume: 45 start-page: 5 issue: 1 year: 1923 ident: 10.1016/j.asoc.2023.110061_b67 article-title: A closed set of normal orthogonal functions publication-title: Amer. J. Math. doi: 10.2307/2387224 – start-page: 42 year: 2019 ident: 10.1016/j.asoc.2023.110061_b62 article-title: Combinatorial surrogate-assisted optimization for bus stops spacing problem – volume: 28 start-page: 58 issue: 1 year: 2014 ident: 10.1016/j.asoc.2023.110061_b77 article-title: The unconstrained binary quadratic programming problem: A survey publication-title: J. Comb. Optim. doi: 10.1007/s10878-014-9734-0 – start-page: 573 year: 2016 ident: 10.1016/j.asoc.2023.110061_b32 article-title: A generative kriging surrogate model for constrained and unconstrained multi-objective optimization – volume: 50 start-page: 536 issue: 2 year: 2020 ident: 10.1016/j.asoc.2023.110061_b50 article-title: A random forest-assisted evolutionary algorithm for data-driven constrained multiobjective combinatorial optimization of trauma systems publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2018.2869674 – volume: 242 year: 2022 ident: 10.1016/j.asoc.2023.110061_b34 article-title: A classification surrogate-assisted multi-objective evolutionary algorithm for expensive optimization publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2022.108416 – volume: 227 start-page: 331 issue: 2 year: 2013 ident: 10.1016/j.asoc.2023.110061_b75 article-title: On the structure of multiobjective combinatorial search space: MNK-landscapes with correlated objectives publication-title: European J. Oper. Res. doi: 10.1016/j.ejor.2012.12.019 – volume: 1 start-page: 1 issue: 2 year: 2021 ident: 10.1016/j.asoc.2023.110061_b63 article-title: A novel approach to designing surrogate-assisted genetic algorithms by combining efficient learning of Walsh coefficients and dependencies publication-title: ACM Trans. Evol. Learn. Optim. doi: 10.1145/3453141 – year: 2018 ident: 10.1016/j.asoc.2023.110061_b38 – start-page: 3773 year: 2020 ident: 10.1016/j.asoc.2023.110061_b65 article-title: Optimizing discrete spaces via expensive evaluations: A learning to search framework – start-page: 303 year: 2019 ident: 10.1016/j.asoc.2023.110061_b57 article-title: Walsh functions as surrogate model for Pseudo-Boolean optimization problems – volume: 24 start-page: 5 issue: 1–2 year: 2017 ident: 10.1016/j.asoc.2023.110061_b9 article-title: Surrogate-assisted multicriteria optimization: Complexities, prospective solutions, and business case publication-title: J. Multi-Criteria Decis. Anal. doi: 10.1002/mcda.1605 – volume: vol. 12 year: 1998 ident: 10.1016/j.asoc.2023.110061_b10 – volume: 11 start-page: 712 issue: 6 year: 2007 ident: 10.1016/j.asoc.2023.110061_b22 article-title: MOEA/D: A multiobjective evolutionary algorithm based on decomposition publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2007.892759 – volume: 45 start-page: 5 issue: 1 year: 2001 ident: 10.1016/j.asoc.2023.110061_b20 article-title: Random forests publication-title: Mach. Learn. doi: 10.1023/A:1010933404324 – volume: 181 start-page: 1670 issue: 3 year: 2007 ident: 10.1016/j.asoc.2023.110061_b74 article-title: Working principles, behavior, and performance of MOEAs on MNK-landscapes publication-title: European J. Oper. Res. doi: 10.1016/j.ejor.2006.08.004 – volume: 8 start-page: 2699 year: 2021 ident: 10.1016/j.asoc.2023.110061_b44 article-title: Surrogate-assisted evolutionary algorithm for expensive constrained multi-objective discrete optimization problems publication-title: Complex Intell. Syst. doi: 10.1007/s40747-020-00249-x – volume: 21 start-page: 440 issue: 3 year: 2017 ident: 10.1016/j.asoc.2023.110061_b21 article-title: A survey of multiobjective evolutionary algorithms based on decomposition publication-title: IEEE Trans. Evol. Comput. |
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| Snippet | The aim of this paper is to study surrogate-assisted algorithms for expensive multiobjective combinatorial optimization problems. Targeting pseudo-boolean... |
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| SubjectTerms | Artificial Intelligence Computer Science Decomposition Discrete surrogates Multi-objective optimization Operations Research |
| Title | Walsh-based surrogate-assisted multi-objective combinatorial optimization: A fine-grained analysis for pseudo-boolean functions |
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