In this paper, we have proposed a new genetic algorithm for p-median location problem. In this regard, prior genetic algorithms were designed for p-median location problem by proposing several methods that are used in generation of initial population, crossover and mutation operators, and new operator socalled re-allocation has been incorporated into the algorithm that causes to find the optima...

Heuristic concentration (HC) is a two-stage metaheuristic that can be applied to a wide variety of combinatorial problems. It is particularly suited to location problems in which the number of facilities is given in advance. In such settings, the ®rst stage of HC repeatedly applies some random-start interchange (or other) heuristic to produce a number of alternative facility con®gurations. A su...

Metaheuristics represent an important class of techniques to solve, approximately, hard combinatorial optimization problems for which the use of exact methods is impractical. In this work, we propose a hybrid version of the GRASP metaheuristic, which incorporates a data mining process, to solve the p-median problem. We believe that patterns obtained by a data mining technique, from a set of sub...

Scatter search is a population-based method that has been shown to yield high-quality outcomes for combinatorial optimization problems. It uses strategies for combining solution vectors that have proved effective in a variety of problem settings. In this paper, we present a scatter search implementation for an NP-hard variant of the classic p-hub median problem. Specifically, we tackle the unca...

In this paper we present a neural network model and new formulation for the p-median problem. The effectiveness and efficiency of our algorithm under varying problem sizes are analyzed in comparison to conventional heuristic methods. The results for small-scale problems (less than 100 points) indicate that our implementation of algorithm is effective. Furthermore, we also have applied our algor...

The Capacitated p-median problem (CPMP) seeks to solve the optimal location of p facilities, considering distances and capacities for the service to be given by each median. In this paper we present a column generation approach to CPMP. The identified restricted master problem optimizes the covering of 1-median clusters satisfying the capacity constraints, and new columns are generated consider...

† Département d’informatique et recherche opérationnelle and Centre de recherche sur les transports, Université de Montréal Email: {hoeb, michelg}@crt.umontreal.ca ‡ GERAD and École des Hautes Etudes Commerciales 3000 ch. de la Côte-Sainte-Catherine, Montréal H3T 1V6, Canada Email: {pierreh, nenad}@crt.umontreal.ca § Matematički Institut, SANU Knez Mihajlova 35, Beograd, Yugoslavia Email: nenad...

The paper is aimed at experimental evaluation of the complexity of the p-Median problem instances, defined by m × n costs matrices, from several of the most widely used libraries. The complexity is considered in terms of possible problem size reduction and preprocessing, irrespective of the solution algorithm. We use a pseudo-Boolean representation of PMP instances that allows several reduction...

In this paper we consider the well known p-median problem. We study the behavior of the local improvement algorithm with a new large neighborhood. Computational experiments on the difficult instances show that the algorithm with the neighborhood is fast and finds feasible solutions with small relative error.

We study a well-known linear programming relaxation of the p-median problem. We give a characterization of the directed graphs for which this system of inequalities defines an integral polytope. As a consequence, we obtain that the p-median problem is polynomial in that class of graphs. We also give an algorithm to recognize these graphs. © 2011 Elsevier B.V. All rights reserved.