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An Effective Ant Colony Optimization Algorithm for the Minimum Sum Coloring Problem

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Computational Collective Intelligence. Technologies and Applications (ICCCI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8083))

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Abstract

Ant colony optimization is a collective problem solving approach that simulates the foraging behavior of ants. It is a class of metaheuristics which made a success in NP-hard combinational optimization problems. In this paper we study the minimum sum coloring problem (MSCP), which is an NP-hard problem derived from the graph coloring problem (GCP). The goal of this problem is to minimize the sum of colors used in a graph. We propose for this problem a method based on ant colony optimization, which we tested on several benchmark graphs from the usual literature. By comparing the test results with those found in the literature, we demonstrate the effectiveness of the proposed method.

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Author information

Authors and Affiliations

  1. Research Laboratory Mathematics, Computing and Applications, Faculty of Sciences, University of Mohammed V-Agdal, Rabat, Morocco

    Sidi Mohamed Douiri & Souad Elbernoussi

Authors
  1. Sidi Mohamed Douiri
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  2. Souad Elbernoussi
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Editor information

Editors and Affiliations

  1. Computer and Information Technology Department, University of Craiova, Bvd. Decebal 107, 200440, Craiova, Romania

    Costin Bǎdicǎ

  2. Institute of Informatics, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Ngoc Thanh Nguyen

  3. Computer and Information Technology Department, University of Craiova, Bvd. Decebal 107, 200440, Craiova, Romania

    Marius Brezovan

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Douiri, S.M., Elbernoussi, S. (2013). An Effective Ant Colony Optimization Algorithm for the Minimum Sum Coloring Problem. In: Bǎdicǎ, C., Nguyen, N.T., Brezovan, M. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2013. Lecture Notes in Computer Science(), vol 8083. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40495-5_35

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  • DOI: https://doi.org/10.1007/978-3-642-40495-5_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40494-8

  • Online ISBN: 978-3-642-40495-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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