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New Evolutionary Genetic Algorithms for Combinatorial Optimization Problems

  • Do Thi Loan
  • Fam Quang Bac
Conference paper

Abstract

This paper deals with the NP-complete combinatorial optimization problems. A large number of papers has been devoted to them. A traditional approach of Operational Research has been used (Lawler et al. 1985). Kirkpatrick et al. (1983) used Simulated Annealing. Hopfield and Tank (1985) applied a neural networks for finding suboptimal solution for TSP. In recent years interest has raised to apply evolutionary algorithms to combinatorial optimization problems (Holland 1975; Brady 1985).

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References

  1. Brady, R.M. (1985), Optimization strategies gleaned from natural evolution. Nature 317: 804–906.CrossRefGoogle Scholar
  2. Goldberg, D.E., Lingle, R. (1985), Alleles, loci, and the traveling salesman problem. In Proc. Int. com. on Genetic Algorithms and their Applications. Carnegie Mellon University, Pittsburgh, pp. 154–159.Google Scholar
  3. Holland, J.H. (1975) Adaption in nature and artificial systems. University of Michigan Press, Ann Arbor.Google Scholar
  4. Hopfield, J.J., Tank, D.W. (1985), “Neural” computation of decisions in optimization problems. Biol cybern 52: 141–152.Google Scholar
  5. Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P. (1983), Optimization by simulates annealing. Science 220: 671–680.CrossRefGoogle Scholar
  6. Lawler, E.L., Lenstra, J.K., Rinnooy, Kan A.H.G. (1985), The traveling salesman problem. Wiley, New York.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Do Thi Loan
    • 1
  • Fam Quang Bac
    • 1
  1. 1.Department of Flexible Manufacturing SystemsMendeleev Institute of Chemical EngineeringMoscowRussia

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