Genetic Local Search in Combinatorial Optimization

  title={Genetic Local Search in Combinatorial Optimization},
  author={Antoon W. J. Kolen and Erwin Pesch},
  journal={Discrete Applied Mathematics},
As the name suggests genetic algorithms are motivated by the theory of evolution, see [S, 9, 19,25,27]. In contrast to local search algorithms such as simulated annealing [l] and tabu search [6,7], which are based on manipulating one feasible solution, a genetic algorithm considers a population of feasible solutions. Working with populations permits us to identify and explore properties which good solutions have in common. In the early work on genetic algorithms a solution is encoded as a… CONTINUE READING


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