A Continuous Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem

  • Mehmet Sevkli
  • Ali R. Guner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4150)


In this paper, a continuous Particle Swarm Optimization (PSO) algorithm is presented for the Uncapacitated Facility Location (UFL) problem. In order to improve the solution quality a local search is embedded to the PSO algorithm. It is applied to several benchmark suites collected from OR-library. The results are presented and compared to the results of two recent metaheuristic approaches, namely Genetic Algorithm(GA) and Evolutionary Simulated Annealing (ESA). It is concluded that the PSO algorithm is better than the compared methods and generates more robust results.


Particle Swarm Optimization Local Search Position Vector Particle Swarm Optimization Algorithm Local Search Algorithm 
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

  • Mehmet Sevkli
    • 1
  • Ali R. Guner
    • 2
  1. 1.Department of Industrial EngineeringFatih UniversityIstanbulTurkey
  2. 2.Department of Industrial and Manufacturing EngineeringWayne State UniversityDetroitUSA

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