Combining Tabu Search and Genetic Algorithms to Solve the Capacitated Multicommodity Network Flow Problem

Carolina LAGOS¹, Broderick CRAWFORD¹, Ricardo SOTO²,
Jose-Miguel RUBIO¹, Enrique CABRERA¹, Fernando PARADES³
¹Pontificia Universidad Católica de Valparaíso,
2340025 Valparaíso, Chile carolina.lagos@mail.pucv.cl
²CIMFAV, Universidad de Valparaíso,
Valparaíso, Chile
³Escuela de Ingeniería Industrial, Universidad Diego Portales,
8370179 Santiago, Chile

Abstract: Network design has been an important issue in logistics during the last century. This is due to the significant impact that an efficient distribution network design can have over both costs and service level. In this article, we present a heuristic solution approach for the well-known capacitated multicommodity network flow problem. The heuristic approach combines two well-known algorithms namely Tabu Search and Genetic Algorithms. While the main algorithm is Tabu Search, the Genetic Algorithm is used to select the best option among the neighbours of the current solution. To be able to do that some well-known evolutionary operators such as cross-over and mutation are made use of. This hybrid approach obtains important improvements when compared to the ones presented previously in the literature.

Keywords: Multicommodity network flow problem, network design, probabilistic neighbour selection criterion, tabu search, genetic algorithms.

>>Full Text
CITE THIS PAPER AS:
Carolina LAGOS, Broderick CRAWFORD, Enrique CABRERA, Ricardo SOTO, Jose-Miguel RUBIO, Fernando PARADES, Combining Tabu Search and Genetic Algorithms to Solve the Capacitated Multicommodity Network Flow Problem, Studies in Informatics and Control, ISSN 1220-1766, vol. 23 (3), pp. 265-276, 2014. https://doi.org/10.24846/v23i3y201405