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Hybrid Methods

In: Optimization Under Stochastic Uncertainty

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  • Kurt Marti

    (University of Bundeswehr Munich)

Abstract

Depending on the type of the random search method, it may happen that the procedure finds rather fast a local extremum x l o c ∗ $$x_{loc}^{\ast }$$ of the objective function f under consideration, but get then stuck in this point. On the other hand, there are procedures having features to omit this behavior. For example, a special property of simulated annealing methods is that also non-improving steps are possible with decreasing probability (cooling). Thus, steps out of the neighborhood of a local extremum are possible with a certain probability.

Suggested Citation

  • Kurt Marti, 2020. "Hybrid Methods," International Series in Operations Research & Management Science, in: Optimization Under Stochastic Uncertainty, chapter 0, pages 327-337, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-55662-4_17
    DOI: 10.1007/978-3-030-55662-4_17
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