Very large-scale neighborhood search for solving multiobjective combinatorial optimization problems

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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. © 2011 Springer-Verlag.

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Lust, T., Teghem, J., & Tuyttens, D. (2011). Very large-scale neighborhood search for solving multiobjective combinatorial optimization problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6576 LNCS, pp. 254–268). https://doi.org/10.1007/978-3-642-19893-9_18

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