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- W1995780467 abstract "In this paper, we formalize a multiobjective local search paradigm by combining set-based multiobjective optimization and neighborhood-based search principles. Approximating the Pareto set of a multiobjective optimization problem has been recently defined as a set problem, in which the search space is made of all feasible solution-sets. We here introduce a general set-based local search algorithm, explicitly based on a set-domain search space, evaluation function, and neighborhood relation. Different classes of set-domain neighborhood structures are proposed, each one leading to a different set-based local search variant. The corresponding methodology generalizes and unifies a large number of existing approaches for multiobjective optimization. Preliminary experiments on multiobjective NK-landscapes with objective correlation validates the ability of the set-based local search principles. Moreover, our investigations shed the light to further research on the efficient exploration of large-size set-domain neighborhood structures." @default.
- W1995780467 created "2016-06-24" @default.
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- W1995780467 date "2013-07-06" @default.
- W1995780467 modified "2023-10-18" @default.
- W1995780467 title "On set-based local search for multiobjective combinatorial optimization" @default.
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- W1995780467 doi "https://doi.org/10.1145/2463372.2463430" @default.
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