A population-based local search for solving a bi-objective vehicle routing problem

Authors:
Joseph M. Pasia;Karl F. Doerner;Richard F. Hartl;Marc Reimann
Affiliations:
Department of Mathematics, University of the Philippines-Diliman, Quezon City, Philippines and Department of Management Science, University of Vienna, Vienna, Austria;Department of Management Science, University of Vienna, Vienna, Austria;Department of Management Science, University of Vienna, Vienna, Austria;Institute for Operations Research, ETH Zurich, Zurich, Switzerland
Venue:
EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
Year:
2007

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Abstract

In this paper we present a population-based local search for solving a bi-objective vehicle routing problem. The objectives of the problem are minimization of the tour length and balancing the routes. The algorithm repeatedly generates a pool of good initial solutions by using a randomized savings algorithm followed by local search. The local search uses three neighborhood structures and evaluates the fitness of candidate solutions using dominance relation. Several test instances are used to assess the performance of the new approach. Computational results show that the population-based local search outperforms the best known algorithm for this problem.