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Integrating tabu search and VLSN search to develop enhanced algorithms: A case study using bipartite boolean quadratic programs

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  • Glover, Fred
  • Ye, Tao
  • Punnen, Abraham P.
  • Kochenberger, Gary

Abstract

The bipartite boolean quadratic programming problem (BBQP) is a generalization of the well studied boolean quadratic programming problem. The model has a variety of real life applications; however, empirical studies of the model are not available in the literature, except in a few isolated instances. In this paper, we develop efficient heuristic algorithms based on tabu search, very large scale neighborhood (VLSN) search, and a hybrid algorithm that integrates the two. The computational study establishes that effective integration of simple tabu search with VLSN search results in superior outcomes, and suggests the value of such an integration in other settings. Complexity analysis and implementation details are provided along with conclusions drawn from experimental analysis. In addition, we obtain solutions better than the best previously known for almost all medium and large size benchmark instances.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:241:y:2015:i:3:p:697-707
    DOI: 10.1016/j.ejor.2014.09.036
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. GILLIS, Nicolas & GLINEUR, François, 2010. "Low-rank matrix approximation with weights or missing data is NP-hard," LIDAM Discussion Papers CORE 2010075, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. 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.
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    Cited by:

    1. Zeng, Zhizhong & Yu, Xinguo & He, Kun & Huang, Wenqi & Fu, Zhanghua, 2016. "Iterated Tabu Search and Variable Neighborhood Descent for packing unequal circles into a circular container," European Journal of Operational Research, Elsevier, vol. 250(2), pages 615-627.
    2. 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.
    3. 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.
    4. Vladyslav Sokol & Ante Ćustić & Abraham P. Punnen & Binay Bhattacharya, 2020. "Bilinear Assignment Problem: Large Neighborhoods and Experimental Analysis of Algorithms," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 730-746, July.
    5. Karapetyan, Daniel & Punnen, Abraham P. & Parkes, Andrew J., 2017. "Markov Chain methods for the Bipartite Boolean Quadratic Programming Problem," European Journal of Operational Research, Elsevier, vol. 260(2), pages 494-506.
    6. Wang, Yang & Wu, Qinghua & Glover, Fred, 2017. "Effective metaheuristic algorithms for the minimum differential dispersion problem," European Journal of Operational Research, Elsevier, vol. 258(3), pages 829-843.

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