Stochastic local search algorithms: An overview

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Abstract

In this chapter, we give an overview of the main concepts underlying the stochastic local search (SLS) framework and outline some of the most relevant SLS techniques. We also discuss some major recent research directions in the area of stochastic local search. The remainder of this chapter is structured as follows. In Sect. 54.1, we situate the notion of SLS within the broader context of fundamental search paradigms and briefly review the definition of an SLS algorithm. In Sect. 54.2, we summarize the main issues and trends in the design of greedy constructive and iterative improvement algorithms, while in Sects. 54.3-54.5, we provide a concise overview of some of the most widely used simple, hybrid, and population-based SLS methods. Finally, in Sect. 54.6, we discuss some recent topics of interest, such as the systematic design of SLS algorithms and methods for the automatic configuration of SLS algorithms.

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Hoos, H. H., & Stützle, T. (2015). Stochastic local search algorithms: An overview. In Springer Handbook of Computational Intelligence (pp. 1085–1105). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_54

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