This paper presents two different Ant System ( AS) based algorithms for the Capacitated Fixed Charge Location Problem (CFCLP) which is a discrete facility location problem that consists of selecting a subset of facilities that must completely supply a set of customers at a minimum cost. The first algorithm is concerned with extending and improving existing work primarily by introducing a previously unconsidered local search scheme based on pheromone intensity. Whilst, the second method makes a transformation of the derived AS algorithm into the hyper-cube famework in an attempt to improve efficiency and robustness. Computational results for a series of standard benchmark problems are presented and indicate that the proposed methods are capable of deriving optimal solutions for the CFCLP. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Venables, H., & Moscardini, A. (2008). Ant based heuristics for the capacitated fixed charge location problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5217 LNCS, pp. 235–242). https://doi.org/10.1007/978-3-540-87527-7_22
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