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An Adaptive Search Heuristic for the Capacitated Fixed Charge Location Problem

  • Harry Venables
  • Alfredo Moscardini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4150)

Abstract

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.

Keywords

Local Search Transportation Problem Operational Research Society Capacitate Facility Location Problem Plant Location Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Harry Venables
    • 1
  • Alfredo Moscardini
    • 2
  1. 1.Sunderland Business SchoolUniversity of SunderlandUnited Kingdom
  2. 2.School of Computing & TechnologyUniversity of SunderlandUnited Kingdom

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