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Handbook of Natural Computing pp 1623–1655Cite as

Simulated Annealing

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Abstract

Since its introduction as a generic heuristic for discrete optimization in 1983, simulated annealing (SA) has become a popular tool for tackling both discrete and continuous problems across a broad range of application areas. This chapter provides an overview of the technique with the emphasis being on the use of simulated annealing in the solution of practical problems. A detailed statement of the algorithm is given, together with an explanation of its inspiration from the field of statistical thermodynamics. This is followed by a brief overview of the theory with emphasis on those results that are important to the decisions that need to be made for a practical implementation. It then goes on to look at some of the ways in which the basic algorithm has been modified in order to improve its performance in the solution of a variety of problems. It also includes a brief section on application areas and concludes with general observations and pointers to other sources of information such as survey articles and websites offering downloadable simulated annealing code.

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Authors and Affiliations

  1. Gower Optimal Algorithms, Ltd., Swansea, UK

    Kathryn A. Dowsland

  2. School of Mathematics, Cardiff University, Cardiff, UK

    Jonathan M. Thompson

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  1. Kathryn A. Dowsland
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  2. Jonathan M. Thompson
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Correspondence to Kathryn A. Dowsland or Jonathan M. Thompson .

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Editors and Affiliations

  1. LIACS, Leiden University, Leiden, The Netherlands

    Grzegorz Rozenberg

  2. Computer Science Department, University of Colorado, Boulder, USA

    Grzegorz Rozenberg

  3. LIACS, Leiden University, Leiden, The Netherlands

    Thomas Bäck

  4. LIACS, Leiden University, Leiden, The Netherlands

    Joost N. Kok

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Dowsland, K.A., Thompson, J.M. (2012). Simulated Annealing. In: Rozenberg, G., Bäck, T., Kok, J.N. (eds) Handbook of Natural Computing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92910-9_49

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