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Integration of Metaheuristics and Constraint Programming

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Springer Handbook of Computational Intelligence

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Abstract

A promising research line in the optimization community regards the hybridization of exact and heuristics methods. In this chapter we survey the specific integration of two complementary optimization paradigms, namely Constraint Programming, for the exact part, and

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Abbreviations

ACO:

ant colony optimization

AI:

artificial intelligence

CBLS:

constraint-based local search

COP:

constrained optimization problem

CP:

constraint programming

CSP:

constraint satisfaction problem

GA:

genetic algorithm

LDS:

limited discrepancy search

LNS:

large neighborhood search

LP:

logic programming

OPL:

open programming language

OR:

operations research

VLNS:

very large neighborhood search

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Authors and Affiliations

  1. Dip. Ingegneria Elettrica, Gestionale e Meccanica, Università degli Studi di Udine, via delle Scienze 208, 33100, Udine, Italy

    Luca Di Gaspero

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  1. Luca Di Gaspero
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Correspondence to Luca Di Gaspero .

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Editors and Affiliations

  1. Systems Research Inst., Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

  2. Dep. Electrical and Computer Engineering, University of Alberta, 116 Street 9107, T6J 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

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Di Gaspero, L. (2015). Integration of Metaheuristics and Constraint Programming. In: Kacprzyk, J., Pedrycz, W. (eds) Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_62

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  • DOI: https://doi.org/10.1007/978-3-662-43505-2_62

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