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Journal Articles Journal of Heuristics Year : 2019

Archivers for the representation of the set of approximate solutions for MOPs

Abstract

In this paper we address the problem of computing suitable representations of the set of approximate solutions of a given multi-objective optimization problem via stochastic search algorithms. For this, we will propose different archiving strategies for the selection of the candidate solutions maintained by the generation process of the stochastic search process, and investigate them further on analytically and empirically. For all archivers we will provide upper bounds on the approximation quality as well as on the cardinality of the limit solution set. We conclude this work by a comparative study on some test problems in order to visualize the effect of all novel archiving strategies.
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Dates and versions

hal-02304717 , version 1 (03-10-2019)

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Oliver Schutze, Carlos Hernandez, El-Ghazali Talbi, Jian-Qiao Sun, Yousef Naranjani, et al.. Archivers for the representation of the set of approximate solutions for MOPs. Journal of Heuristics, 2019, 25 (1), pp.71-105. ⟨10.1007/s10732-018-9383-z⟩. ⟨hal-02304717⟩
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