A study with neighborhood searches to deal with multiobjective unconstrained permutation problems

Abstract

This paper introduces a study with neighborhood search algorithms to deal with unconstrained multiobjective permutation problems. Filter-and-fan/path relinking approach designed by us, and the stochastic local search (SLS) developed by Paquete and Stutzle [22], implemented by us, are compared using as study cases the bi-objective quadratic assignment problem, and the bi-objective travelling salesman problem. Our approach is also compared with results published for bi-objective quadratic assignment problem, bi-objective flow shop problem, bi-objective and tri-objective travelling salesman problems. The results obtained show that the filter-and-fan/path relinking approach seems to be promising to tackle multiobjective permutation problems, achieving good and wide distributed approximations to the Pareto-optimal front.