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Usage of Exact Algorithms to Enhance Stochastic Local Search Algorithms

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Matheuristics

Part of the book series: Annals of Information Systems ((AOIS,volume 10))

Abstract

Exact mathematical programming techniques such as branch-and-bound or dynamic programming and stochastic local search techniques have traditionally been seen as being two general but distinct approaches for the effective solution of combinatorial optimization problems, each having particular advantages and disadvantages. In several research efforts true hybrid algorithms, which exploit ideas from both fields, have been proposed. In this chapter we review some of the main ideas of several such combinations and illustrate them with examples from the literature. Our focus here is on algorithms that have the main framework given by the local search and use exact algorithms to solve subproblems.

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Acknowledgements

This work has been supported by META-X, an ARC project funded by the French Community of Belgium. TS acknowledges support from the fund for scientific research F.R.S.-FNRS of the French Community of Belgium, of which he is a research associate.

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Authors and Affiliations

  1. School of Mathematics, University of New South Wales, Sydney, Australia

    Irina Dumitrescu

  2. IRIDIA, Université Libre de Bruxelles (ULB), Brussels, Belgium

    Thomas Stützle

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  1. Irina Dumitrescu
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Correspondence to Irina Dumitrescu .

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  1. Dipto. Scienze dell‘Informazione, Universitá di Bologna, Contrada Sacchi 3, Cesena, 47023, Italy

    Vittorio Maniezzo

  2. Avenue Franklin Roosevelt 50, Bruxelles, 1050, Belgium

    Thomas Stützle

  3. Dept. Wirtschaftswissenschaften, Inst. Wirtschaftsinformatik, Universität Hamburg, Von-Melle-Park 5, Hamburg, 20146, Germany

    Stefan Voß

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Dumitrescu, I., Stützle, T. (2009). Usage of Exact Algorithms to Enhance Stochastic Local Search Algorithms. In: Maniezzo, V., Stützle, T., Voß, S. (eds) Matheuristics. Annals of Information Systems, vol 10. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1306-7_4

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