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Escaping Local Optima

  • Zbigniew Michalewicz
  • David B. Fogel

Abstract

We’ve discussed a few traditional problem-solving strategies. Some of them guarantee finding the global solution, others don’t, but they all share a common pattern. Either they guarantee discovering the global solution, but are too expensive (i.e., too time consuming) for solving typical real-world problems, or else they have a tendency of “getting stuck” in local optima. Since there is almost no chance to speed up algorithms that guarantee finding the global solution, i.e., there is almost no chance of finding polynomial-time algorithms for most real problems (as they tend to be NP-hard), the other remaining option aims at designing algorithms that are capable of escaping local optima.

Keywords

Local Search Simulated Annealing Local Optimum Tabu Search Current Solution 
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 2000

Authors and Affiliations

  • Zbigniew Michalewicz
    • 1
  • David B. Fogel
    • 2
  1. 1.NuTech Solutions Inc.CharlotteUSA
  2. 2.Natural Selection, Inc.La JollaUSA

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