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International Conference on Contemporary Computing

IC3 2011: Contemporary Computing pp 135–145Cite as

An Efficient EA with Multipoint Guided Crossover for Bi-objective Graph Coloring Problem

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 168))

Abstract

Graph Coloring Problem is a well-studied classical NP-hard combinatorial problem. Several well-known heuristics and evolutionary approaches exist to solve single-objective graph coloring problem. We have considered a bi-objective variant of graph coloring problem, in which the number of colors used and the corresponding penalty which is incurred due to coloring the end-points of an edge with same color, are simultaneously minimized. In this paper, we have presented an evolutionary approach with Multipoint Guided Crossover (MPGX) to minimize both objectives simultaneously. On applying proposed evolutionary algorithm over standard graph coloring problem instances, a guaranteed solution to the single-objective graph coloring problem is achieved. We have adapted a few well-known heuristics which are evolved for single-objective graph coloring problem to generate set of solutions for bi-objective graph coloring problem and obtained Pareto fronts. Empirical results show that proposed evolutionary algorithm with simple Multipoint Guided Crossover generates superior or (near-) equal solutions in comparison with the adapted heuristic solutions as well as with evolutionary algorithm solutions using a few crossover (Penalty-based Color Partitioning Crossover (PCPX) and Degree Based Crossover (DBX)) operators across entire Pareto front for considered bi-objective variant of graph coloring problem.

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Author information

Authors and Affiliations

  1. Dept. of Computer Science & Engineering, Indian Institute of Technology Kharagpur, Kharagpur, WB, 721302, India

    Soma Saha, Gyan Baboo & Rajeev Kumar

Authors
  1. Soma Saha
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  2. Gyan Baboo
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  3. Rajeev Kumar
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Editor information

Editors and Affiliations

  1. Iowa State University and IIT Bombay, India, 329 Durham, Ames, IA 5001, Iowa, USA

    Srinivas Aluru

  2. Indian Statistical Institute, 203 B.T. Road, 700 108, Kolkata, West Bengal, India

    Sanghamitra Bandyopadhyay

  3. The Ohio State University, 3190 Graves Hall, 333 W 10th Ave, 43210, Columbus, OH, USA

    Umit V. Catalyurek

  4. Department of Computing Science, Chalmers University, Rännvagen 6B, 412 96, Göteborg, Sweden

    Devdatt P. Dubhashi

  5. Dept. of Electrical and Computer Engineering, Iowa State University, 329 Durham, IA 50011, Ames, USA

    Phillip H. Jones

  6. TASSL, Dept. of Electrical & Computer Engineering, Rutgers, The State University of New Jersey, Brett Road, NJ 08854-8058, Piscataway, USA

    Manish Parashar

  7. School of Computer Engineering, Nanyang Technological University, N4-02a-32 Nanyang Ave, 639798, Singapore

    Bertil Schmidt

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© 2011 Springer-Verlag Berlin Heidelberg

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Saha, S., Baboo, G., Kumar, R. (2011). An Efficient EA with Multipoint Guided Crossover for Bi-objective Graph Coloring Problem. In: Aluru, S., et al. Contemporary Computing. IC3 2011. Communications in Computer and Information Science, vol 168. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22606-9_17

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  • DOI: https://doi.org/10.1007/978-3-642-22606-9_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22605-2

  • Online ISBN: 978-3-642-22606-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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