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2016 | OriginalPaper | Chapter

Enhanced Metaheuristics with the Multilevel Paradigm for MAX-CSPs

Authors : Noureddine Bouhmala, Mikkel Syse Groesland, Vetle Volden-Freberg

Published in: Computational Science and Its Applications -- ICCSA 2016

Publisher: Springer International Publishing

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Abstract

As many real-world optimization problems become increasingly complex and hard to solve, better optimization algorithms are always needed. Nature inspired algorithms such as genetic algorithms and simulated annealing which belongs to the class of evolutionary algorithms are regarded as highly successful algorithms when applied to a broad range of discrete as well continuous optimization problems. This paper introduces the multilevel paradigm combined with genetic algorithm and simulated annealing for solving the maximum constraint satisfaction problem. The promising performances achieved by the proposed approach is demonstrated by comparisons made to solve conventional random benchmark problems.

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Metadata
Title
Enhanced Metaheuristics with the Multilevel Paradigm for MAX-CSPs
Authors
Noureddine Bouhmala
Mikkel Syse Groesland
Vetle Volden-Freberg
Copyright Year
2016
Book
Computational Science and Its Applications -- ICCSA 2016

Print ISBN: 978-3-319-42088-2

Electronic ISBN: 978-3-319-42089-9

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-42089-9_38

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