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Hybrid Systems

  • Zbigniew Michalewicz
  • David B. Fogel
Chapter

Abstract

We know that no single algorithm can be the best approach to solve every problem. We have to incorporate knowledge about the problem at hand into our algorithm in some useful manner; otherwise, it may not be any better than a random search. One way to approach this issue is to hybridize an evolutionary algorithm with more standard procedures, such as hill-climbing or greedy methods. Individual solutions can be improved using local techniques and then placed back in competition with other members of the population. The initial population can be seeded with solutions that are found with classic methods. There are many ways to form hybrid approaches that marry evolutionary algorithms with other procedures.

Keywords

Evolutionary Algorithm Hybrid System Mobile Agent Pheromone Trail Cooperative Coevolution 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Zbigniew Michalewicz
    • 1
  • David B. Fogel
    • 2
  1. 1.Department of Computer ScienceUniversity of North CarolinaCharlotteUSA
  2. 2.Natural Selection, Inc.La JollaUSA

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