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Very Large-Scale Neighborhood Search for Solving Multiobjective Combinatorial Optimization Problems

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Evolutionary Multi-Criterion Optimization (EMO 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6576))

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Abstract

Very large-scale neighborhood search (VLSNS) is a technique intensively used in single-objective optimization. However, there is almost no study of VLSNS for multiobjective optimization. We show in this paper that this technique is very efficient for the resolution of multiobjective combinatorial optimization problems. Two problems are considered: the multiobjective multidimensional knapsack problem and the multiobjective set covering problem. VLSNS are proposed for these two problems and are integrated into the two-phase Pareto local search. The results obtained on biobjective instances outperform the state-of-the-art results for various indicators.

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Authors and Affiliations

  1. Laboratory of Mathematics & Operational Research, Faculté Polytechnique de Mons, 20, place du parc, 7000, Mons, Belgium

    Thibaut Lust, Jacques Teghem & Daniel Tuyttens

Authors
  1. Thibaut Lust
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  2. Jacques Teghem
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  3. Daniel Tuyttens
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Editor information

Editors and Affiliations

  1. Department of Mathematics, Federal University of Minas Gerais, Av. Antônio Carlos 6627, 31270-901, Belo Horizonte, MG, Brazil

    Ricardo H. C. Takahashi

  2. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, 208 016, Kanpur, India

    Kalyanmoy Deb

  3. Department of Computer Engineering, Centro Federal de Educaçao Tecnológica de Minas Gerais, Av. Amazonas 5253, 30421-169, Belo Horizonte, MG, Brazil

    Elizabeth F. Wanner

  4. Faculty of Economics, University of Catania, Corso Italia 55, 95129, Catania, Italy

    Salvatore Greco

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© 2011 Springer-Verlag Berlin Heidelberg

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Lust, T., Teghem, J., Tuyttens, D. (2011). Very Large-Scale Neighborhood Search for Solving Multiobjective Combinatorial Optimization Problems. In: Takahashi, R.H.C., Deb, K., Wanner, E.F., Greco, S. (eds) Evolutionary Multi-Criterion Optimization. EMO 2011. Lecture Notes in Computer Science, vol 6576. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19893-9_18

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  • DOI: https://doi.org/10.1007/978-3-642-19893-9_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19892-2

  • Online ISBN: 978-3-642-19893-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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