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Combining Metaheuristics and Exact Algorithms in Combinatorial Optimization: A Survey and Classification

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Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach (IWINAC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3562))

Abstract

In this survey we discuss different state-of-the-art approaches of combining exact algorithms and metaheuristics to solve combinatorial optimization problems. Some of these hybrids mainly aim at providing optimal solutions in shorter time, while others primarily focus on getting better heuristic solutions. The two main categories in which we divide the approaches are collaborative versus integrative combinations. We further classify the different techniques in a hierarchical way. Altogether, the surveyed work on combinations of exact algorithms and metaheuristics documents the usefulness and strong potential of this research direction.

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Authors and Affiliations

  1. Institute of Computer Graphics and Algorithms, Vienna University of Technology, Vienna, Austria

    Jakob Puchinger & Günther R. Raidl

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  1. Jakob Puchinger
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  2. Günther R. Raidl
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Editors and Affiliations

  1. E.T.S.I. Informática, Universidad Nacional de Educación a Distancia, 28040, Madrid, Spain

    José Mira

  2. E.T.S. de Ingeniería Informática, Departamento de Intelifencia Artificial, Universidad Nacional de Educación a Distancia, Juan del Rosal, 16, 28040, Madrid, Spain

    José R. Álvarez

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Puchinger, J., Raidl, G.R. (2005). Combining Metaheuristics and Exact Algorithms in Combinatorial Optimization: A Survey and Classification. In: Mira, J., Álvarez, J.R. (eds) Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach. IWINAC 2005. Lecture Notes in Computer Science, vol 3562. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499305_5

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  • DOI: https://doi.org/10.1007/11499305_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26319-7

  • Online ISBN: 978-3-540-31673-2

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