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Analyzing Stochastic Search Algorithms

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Abstract

In this chapter, we introduce the stochastic search algorithms for single-objective optimization that will be subject to the analyses throughout this book. We start by describing algorithms for single-objective optimization problems in Section 4.1. There, we consider different variants of RLS and variants of a well-known evolutionary algorithm called (1+1) EA. Afterwards, we introduce some basic methods methods for analyzing stochastic search algorithms.

Keywords

  • Search Point
  • Cover Time
  • Travel Salesperson Problem
  • Expected Wait Time
  • Stochastic Search 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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Correspondence to Carsten Witt .

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© 2010 Springer-Verlag Berlin Heidelberg

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Neumann, F., Witt, C. (2010). Analyzing Stochastic Search Algorithms. In: Bioinspired Computation in Combinatorial Optimization. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16544-3_4

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  • DOI: https://doi.org/10.1007/978-3-642-16544-3_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16543-6

  • Online ISBN: 978-3-642-16544-3

  • eBook Packages: Computer ScienceComputer Science (R0)