Memetic algorithms for the MinLA problem

  • Authors:
  • Eduardo Rodriguez-Tello;Jin-Kao Hao;Jose Torres-Jimenez

  • Affiliations:
  • LERIA, Université d'Angers, Angers, France;LERIA, Université d'Angers, Angers, France;Mathematics Department, University of Guerrero, Acapulco Guerrero, Mexico

  • Venue:
  • EA'05 Proceedings of the 7th international conference on Artificial Evolution
  • Year:
  • 2005

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Abstract

This paper presents a new Memetic Algorithm designed to compute near optimal solutions for the MinLA problem. It incorporates a highly specialized crossover operator, a fast MinLA heuristic used to create the initial population and a local search operator based on a fine tuned Simulated Annealing algorithm. Its performance is investigated through extensive experimentation over well known benchmarks and compared with other state-of-the-art algorithms.