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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
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
Download citation
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)