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Ant Based Heuristics for the Capacitated Fixed Charge Location Problem

  • Harry Venables
  • Alfredo Moscardini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5217)

Abstract

This paper presents two different \(\mathcal{MAX-MIN}\) Ant System (\(\mathcal{MM}\)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 \(\mathcal{MM}\)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.

Keywords

Location Problem Facility Location Problem Local Search Phase Capacitate Facility Location Problem Unit Transportation Cost 
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 2008

Authors and Affiliations

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

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