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Hybridizing Genetic Algorithms with Branch and Bound Techniques for the Resolution of the TSP

  • C. Cotta
  • J. F. Aldana
  • A. J. Nebro
  • J. M. Troya

Abstract

In this paper some mixed techniques are outlined in order to combine the advantages of two very different methods for the resolution of combinatorial optimization problems (Genetic Algorithms and Branch and Bound Techniques), simultaneously avoiding their drawbacks. Due to the disparity between the basic techniques it is not suitable that they work at the same level so two models have been developed in which each technique assumes the role of being a tool of the other one. Parallelism is an important issue in these techniques.

Keywords

Genetic Algorithm Execution Time Combinatorial Optimization Problem Parallel Execution Hybrid Genetic 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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References

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Copyright information

© Springer-Verlag/Wien 1995

Authors and Affiliations

  • C. Cotta
    • 1
  • J. F. Aldana
    • 1
  • A. J. Nebro
    • 1
  • J. M. Troya
    • 1
  1. 1.Dept. of Lenguajes y Ciencias de la ComputaciónUniv. of MálagaMálagaEspaña

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