A parallel hybrid heuristic for the multicommodity capacitated location problem with balancing requirements

Authors:
Bernard Gendron;Jean-Yves Potvin;Patrick Soriano
Affiliations:
Centre de recherche sur les transports, Université de Montréal and Département d'informatique et de recherche opérationnelle, Université de Montréal, Que., Canada H3C ...;Centre de recherche sur les transports, Université de Montréal and Département d'informatique et de recherche opérationnelle, Université de Montréal, Que., Canada H3C ...;Centre de recherche sur les transports, Université de Montréal and Ecole des Hautes Etudes Commerciales 3000, chemin de la Côte-Sainte-Catherine, Montréal, Que., Canada H3T 2A7
Venue:
Parallel Computing - Special issue: Parallel computing in logistics
Year:
2003

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Abstract

In this paper, a parallel hybrid heuristic is developed for the multicommodity capacitated location problem with balancing requirements. The hybrid involves variable neighborhood descent (VND) and slope scaling (SS). Both methods evolve in parallel within a master-slave architecture where the slave processes communicate through adaptive memories. Numerical results are reported on different types of randomly generated instances, using an increasing number of processors and different distributions of processes between SS and VND.