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Multi-objective variable neighborhood search: an application to combinatorial optimization problems

Abstract : Solutions to real-life optimization problems usually have to be evaluated con-sidering multiple conflicting objectives. These kind of problems, known as multi-objectiveoptimization problems, have been mainly solved in the past by using evolutionary algo-rithms. In this paper, we explore the adaptation of the Variable Neighborhood Search (VNS)metaheuristic to solve multi-objective combinatorial optimization problems. In particular,we describe how to design the shake procedure, the improvement method and the acceptancecriterion within different VNS schemas (Reduced VNS, Variable Neighborhood Descent andGeneral VNS), when two or more objectives are considered. We validate these proposals overtwo multi-objective combinatorial optimization problems
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https://hal-uphf.archives-ouvertes.fr/hal-03401593
Contributor : Mylène Delrue Connect in order to contact the contributor
Submitted on : Monday, October 25, 2021 - 1:56:01 PM
Last modification on : Tuesday, October 26, 2021 - 4:00:31 AM

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Abraham Duarte, Juan Pantrigo, Eduardo Pardo, Nenad Mladenovic. Multi-objective variable neighborhood search: an application to combinatorial optimization problems. Journal of Global Optimization, Springer Verlag, 2015, 63 (3), pp.515-536. ⟨10.1007/s10898-014-0213-z⟩. ⟨hal-03401593⟩

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