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Erschienen in:
2006 | OriginalPaper | Buchkapitel
An Adaptive Search Heuristic for the Capacitated Fixed Charge Location Problem
verfasst von : Harry Venables, Alfredo Moscardini
Erschienen in: Ant Colony Optimization and Swarm Intelligence
Verlag: Springer Berlin Heidelberg
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The Capacitated Fixed Charge Location Problem (CFCLP) consists of selecting a set of facilities that must completely supply a set of customers at a minimum cost. The CFCLP is
NP-hard
thus solution methods are often obtained by using sophisticated techniques. However, if a set of facilities is known a priori then the CFCLP reduces to a transportation problem (TP). Although this can be used to derive solutions by randomly selecting sufficient facilities to be fixed open and noting any cost improvements, it is perceived as a poor technique that does not guarantee solutions near the optimal. This paper presents an adaptive sampling algorithm using Ant Colony Optimization (ACO). We hypothesize that random selection of facilities using ACO will generate at least near-optimal solutions for the CFCLP. Computational results for a series of standard benchmark problems are presented which appear to confirm this hypothesis.