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Hybrid Simulated Annealing for the Bi-objective Quadratic Assignment Problem

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Multi-disciplinary Trends in Artificial Intelligence (MIWAI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10607))

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Abstract

Past research has shown that the performance of algorithms for solving the Quadratic Assignment Problem (QAP) depends on the structure and the size of the instances. In this paper, we study the bi-objective QAP, which is a multi-objective extension of the single-objective QAP to two objectives. The algorithm we propose extends a high-performing Simulated Annealing (SA) algorithm for large-sized, single-objective QAP instances to the bi-objective context. The resulting Hybrid Simulated Annealing (HSA) algorithm is shown to clearly outperform a basic, hybrid iterative improvement algorithm. Experimental results show that HSA clearly outperforms basic Hybrid Iterative Improvement. When compared to state-of-the-art algorithms for the bQAP, a Multi-objective Ant Colony Optimization algorithm and the Strength Pareto Evolutionary Algorithm 2, HSA shows very good performance, outperforms the former in most cases, and showing competitive performance to the latter.

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Acknowledgments

This work was supported by the META-X project, an Action de Recherche Concertée funded by the Scientific Research Directorate of the French Community of Belgium. Mohamed Saifullah Hussin acknowledges support from the Universiti Malaysia Terengganu and Fundamental Research Grant Scheme, Ministry of Higher Education, Malaysia. Thomas Stützle acknowledges support from the Belgian F.R.S.-FNRS, of which he is a Research Associate.

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Authors and Affiliations

  1. SIAM, Universiti Malaysia Terengganu, Kuala Terengganu, Malaysia

    Mohamed Saifullah Hussin

  2. IRIDIA, Université Libre de Bruxelles, Brussels, Belgium

    Thomas Stützle

Authors
  1. Mohamed Saifullah Hussin
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  2. Thomas Stützle
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Correspondence to Mohamed Saifullah Hussin .

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Editors and Affiliations

  1. Universiti Teknologi Brunei, Gadong, Brunei Darussalam

    Somnuk Phon-Amnuaisuk

  2. Universiti Teknologi Brunei, Gadong, Brunei Darussalam

    Swee-Peng Ang

  3. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Soo-Young Lee

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Hussin, M.S., Stützle, T. (2017). Hybrid Simulated Annealing for the Bi-objective Quadratic Assignment Problem. In: Phon-Amnuaisuk, S., Ang, SP., Lee, SY. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2017. Lecture Notes in Computer Science(), vol 10607. Springer, Cham. https://doi.org/10.1007/978-3-319-69456-6_38

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  • DOI: https://doi.org/10.1007/978-3-319-69456-6_38

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  • Print ISBN: 978-3-319-69455-9

  • Online ISBN: 978-3-319-69456-6

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