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