Evolutionary Simulated Annealing Algorithms for Uncapacitated Facility Location Problems

  • Vecihi Yigit
  • M. Emin Aydin
  • Orhan Turkbey
Conference paper


Simulated annealing (SA) is one of the potentially powerful probabilistic metaheuristics to solve large-scale combinatorial optimisation problems. The main drawback with this metaheuristic is its time consuming nature, although it gives more confidence to reach the global optimum. The aim of this paper is to examine an evolutionary approach to simulated annealing for Uncapacitated Facility Location (UFL) problems with some useful comparisons with the latest genetic algorithm approach by [17]. The approach presented in this paper seeks to combine the power of both SA and the evolutionary approach to get a desirable quality of solution within a shorter time. For this purpose, SA is incorporated with evolutionary approach in order to cut down the processing time needed.


Simulated Annealing Location Problem Evolutionary Approach Simulated Annealing Algorithm Neighbourhood Function 
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 London 2004

Authors and Affiliations

  • Vecihi Yigit
    • 1
  • M. Emin Aydin
    • 2
  • Orhan Turkbey
    • 3
  1. 1.Faculty of Engineering, Dept. of Industrial EngineeringAtaturk UniversityErzurumTurkey
  2. 2.Advanced Computation for Design and Decision making Group, Frenchey CampusUniversity of the West of EnglandBristolUK
  3. 3.Dept. of Industrial EngineeringGazi UniversityAnkaraTurkey

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