In this paper, we examine the p-median problem from a bi-objective point of view. Since this is a NP-Hard problem, an efficient algorithm based on the Iterated Local Search heuristic (ILS) is proposed to determine non-dominated solutions (an approximation of the Pareto-optimal solutions). ILS is a simple and powerful stochastic method that has shown very good results for a variety of single-objective combinatorial problems. In each component of the ILS, we use the concept of Pareto dominance. An intensification component based on the Path-Relinking is used to improve the quality of the found non-dominated solutions. To test the performance of the proposed algorithm, we develop a Mathematical Programming Algorithm, called ε-Constraint, that finds a subset of Pareto-optimal solutions by solving iteratively the mathematical model of the problem with additional constraints. The results show that the proposed approach is able to generate good approximations to the non-dominated frontier of the bi-objective problem efficiently. © 2011 Springer-Verlag.
CITATION STYLE
Arroyo, J. E. C., Santos, A. G., Dos Santos, P. M., & Ribeiro, W. G. (2011). A bi-objective iterated local search heuristic with path-relinking for the p-median problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6576 LNCS, pp. 492–504). https://doi.org/10.1007/978-3-642-19893-9_34
Mendeley helps you to discover research relevant for your work.