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A hybrid metaheuristic approach to solving the UBQP problem

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  • Lü, Zhipeng
  • Glover, Fred
  • Hao, Jin-Kao

Abstract

This paper presents a hybrid metaheuristic approach (HMA) for solving the unconstrained binary quadratic programming (UBQP) problem. By incorporating a tabu search procedure into the framework of evolutionary algorithms, the proposed approach exhibits several distinguishing features, including a diversification-based combination operator and a distance-and-quality based replacement criterion for pool updating. The proposed algorithm is able to easily obtain the best known solutions for 31 large random instances up to 7000 variables (which no previous algorithm has done) and find new best solutions for three of nine instances derived from the set-partitioning problem, demonstrating the efficacy of our proposed algorithm in terms of both solution quality and computational efficiency. Furthermore, some key elements and properties of the HMA algorithm are also analyzed.

Suggested Citation

  • Lü, Zhipeng & Glover, Fred & Hao, Jin-Kao, 2010. "A hybrid metaheuristic approach to solving the UBQP problem," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1254-1262, December.
    • Handle: RePEc:eee:ejores:v:207:y:2010:i:3:p:1254-1262
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    References listed on IDEAS

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    1. Mauricio G.C. Resende & Celso C. Ribeiro & Fred Glover & Rafael Martí, 2010. "Scatter Search and Path-Relinking: Fundamentals, Advances, and Applications," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 87-107, Springer.
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    4. Fred Glover & Gary A. Kochenberger & Bahram Alidaee, 1998. "Adaptive Memory Tabu Search for Binary Quadratic Programs," Management Science, INFORMS, vol. 44(3), pages 336-345, March.
    5. Gary Kochenberger & Fred Glover & Bahram Alidaee & Cesar Rego, 2005. "An Unconstrained Quadratic Binary Programming Approach to the Vertex Coloring Problem," Annals of Operations Research, Springer, vol. 139(1), pages 229-241, October.
    6. Katayama, Kengo & Narihisa, Hiroyuki, 2001. "Performance of simulated annealing-based heuristic for the unconstrained binary quadratic programming problem," European Journal of Operational Research, Elsevier, vol. 134(1), pages 103-119, October.
    7. Gintaras Palubeckis, 2004. "Multistart Tabu Search Strategies for the Unconstrained Binary Quadratic Optimization Problem," Annals of Operations Research, Springer, vol. 131(1), pages 259-282, October.
    8. Alidaee, Bahram & Kochenberger, Gary & Lewis, Karen & Lewis, Mark & Wang, Haibo, 2008. "A new approach for modeling and solving set packing problems," European Journal of Operational Research, Elsevier, vol. 186(2), pages 504-512, April.
    9. Glover, Fred & Alidaee, Bahram & Rego, Cesar & Kochenberger, Gary, 2002. "One-pass heuristics for large-scale unconstrained binary quadratic problems," European Journal of Operational Research, Elsevier, vol. 137(2), pages 272-287, March.
    10. Mark Lewis & Bahram Alidaee & Fred Glover & Gary Kochenberger, 2009. "A note on xQx as a modelling and solution framework for the Linear Ordering Problem," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 5(2), pages 152-162.
    11. Alkhamis, Talal M. & Hasan, Merza & Ahmed, Mohamed A., 1998. "Simulated annealing for the unconstrained quadratic pseudo-Boolean function," European Journal of Operational Research, Elsevier, vol. 108(3), pages 641-652, August.
    12. Lodi, Andrea & Allemand, Kim & Liebling, Thomas M., 1999. "An evolutionary heuristic for quadratic 0-1 programming," European Journal of Operational Research, Elsevier, vol. 119(3), pages 662-670, December.
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    Cited by:

    1. Michele Samorani & Yang Wang & Yang Wang & Zhipeng Lv & Fred Glover, 2019. "Clustering-driven evolutionary algorithms: an application of path relinking to the quadratic unconstrained binary optimization problem," Journal of Heuristics, Springer, vol. 25(4), pages 629-642, October.
    2. Wu, Qinghua & Hao, Jin-Kao, 2013. "A hybrid metaheuristic method for the Maximum Diversity Problem," European Journal of Operational Research, Elsevier, vol. 231(2), pages 452-464.
    3. Punnen, Abraham P. & Wang, Yang, 2016. "The bipartite quadratic assignment problem and extensions," European Journal of Operational Research, Elsevier, vol. 250(3), pages 715-725.
    4. Zhang-Hua Fu & Jin-Kao Hao, 2015. "Dynamic Programming Driven Memetic Search for the Steiner Tree Problem with Revenues, Budget, and Hop Constraints," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 221-237, May.
    5. Qinghua Wu & Yang Wang & Fred Glover, 2020. "Advanced Tabu Search Algorithms for Bipartite Boolean Quadratic Programs Guided by Strategic Oscillation and Path Relinking," INFORMS Journal on Computing, INFORMS, vol. 32(1), pages 74-89, January.
    6. Wang, Yang & Lü, Zhipeng & Glover, Fred & Hao, Jin-Kao, 2012. "Path relinking for unconstrained binary quadratic programming," European Journal of Operational Research, Elsevier, vol. 223(3), pages 595-604.
    7. Glover, Fred & Ye, Tao & Punnen, Abraham P. & Kochenberger, Gary, 2015. "Integrating tabu search and VLSN search to develop enhanced algorithms: A case study using bipartite boolean quadratic programs," European Journal of Operational Research, Elsevier, vol. 241(3), pages 697-707.
    8. Zhou, Qing & Benlic, Una & Wu, Qinghua & Hao, Jin-Kao, 2019. "Heuristic search to the capacitated clustering problem," European Journal of Operational Research, Elsevier, vol. 273(2), pages 464-487.

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