Applying bio-inspired techniques to the p-median problem

  • Authors:
  • E. Domínguez;J. Muñoz

  • Affiliations:
  • Department of Computer Science, E.T.S.I.Informatica, University of Malaga, Malaga, Spain;Department of Computer Science, E.T.S.I.Informatica, University of Malaga, Malaga, Spain

  • Venue:
  • IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
  • Year:
  • 2005

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Abstract

Neural networks (NNs) and genetic algorithms (GAs) are the two most popular bio-inspired techniques. Criticism of these approaches includes the tendency of recurrent neural networks to produce infeasible solutions, the lack of generalize of the self-organizing approaches, and the requirement of tuning many internal parameters and operators of genetic algorithms. This paper proposes a new technique which enables feasible solutions, removes the tuning phase, and improves solutions quality of typical combinatorial optimization problems as the p-median problem. Moreover, several biology inspired approaches are analyzed for solving traditional benchmarks.