Carolina LAGOS1,*, Fernando PAREDES2, Stefanie NIKLANDER3,4, Enrique CABRERA5
1 Pontificia Universidad Católica de Valparaíso, Chile
2 Universidad Diego Portales, Escuela de Ingeniería Industrial, Chile
3 Universidad Autónoma de Chile, Chile
4 Universidad Científica del Sur, Peru
5 Universidad de Valparaíso, CIMFAV, Chile
Abstract: Distribution network design (DND) attempts to integrate tactical issues such as inventory policies and/or vehicle routing decisions with strategic ones such as the problem of locating facilities and allocate customers to such facilities. When inventory policy decision making is considered the problem is also known as inventory location modelling (ILM) problem. During the last two decades, mathematical programming as well as (meta-)heuristic approaches have been considered to address different DND problem. In this article we consider a hybrid algorithm of Lagrangian Relaxation and artificial ants to solve an ILM problem previously proposed in the literature. We use ACS to allocate customers to a subset of warehouses that is previously generated by the Lagrangian relaxation. Results show that the hybrid approach is quite competitive, obtaining near-optimal solutions within an acceptable time.
Keywords:Distribution Network Design, Matheuristics, Ant Colony Optimization, Lagrangian Relaxation.
CITE THIS PAPER AS:
Carolina LAGOS*, Fernando PAREDES, Stefanie NIKLANDER, Enrique CABRERA, Solving a Distribution Network Design Problem by Combining Ant Colony Systems and Lagrangian Relaxatio, Studies in Informatics and Control, ISSN 1220-1766, vol. 24 (3), pp. 251-260, 2015. https://doi.org/10.24846/v24i3y201502