On local search for bi-objective knapsack problems

Arnaud Liefooghe (1, 2) , Luis Paquete (3) , José Rui Figueira (4, 5)

1 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
2 LIFL - Laboratoire d'Informatique Fondamentale de Lille
3 ECOS Group - Evolutionary and Complex Systems Group
4 CEG - IST - Center for Management Studies, Instituto Superior Técnico [Porto Salvo]
5 ORCHIDS - Operations research for Complex HybrId Decision Sytems

In this article, a local search approach is proposed for three variants of the bi-objective binary knapsack problem, with the aim of maximizing the total profit and minimizing the total weight. First, an experimental study on a given structural property of connectedness of the efficient set is conducted. Based on this property, a local search algorithm is proposed and its performance is compared against exact algorithms in terms of running time and quality metrics. The experimental results indicate that this simple local search algorithm is able to find a representative set of optimal solutions in most of the cases, and in much less time than exact algorithms.

Mots clés: Multi-objective combinatorial optimization; population-based local search; structural analysis; connectedness; knapsack problems

Domaines: Recherche opérationnelle [math.OC]

Arnaud Liefooghe, Luis Paquete, José Rui Figueira. On local search for bi-objective knapsack problems. Evolutionary Computation, 2013, 21 (1), pp.179-196. ⟨10.1162/EVCO_a_00074⟩. ⟨hal-00676625⟩