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Nested Partitions and Its Applications to the Intermodal Hub Location Problem

In: Optimization and Logistics Challenges in the Enterprise

Author

Listed:
  • Weiwei Chen

    (University of Wisconsin-Madison)

  • Liang Pi

    (University of Wisconsin-Madison)

  • Leyuan Shi

    (University of Wisconsin-Madison)

Abstract

Summary The nested partitions (NP) method has been proven to be a useful framework for effectively solving large-scale discrete optimization problems. In this chapter, we provide a brief review of the NP method and its applications. We then present a hybrid algorithm that integrates mathematical programming with the NP framework. The efficiency of the hybrid algorithm is demonstrated by the intermodal hub location problem (IHLP), a class of discrete facility location problems. Computational results show that the hybrid approach is superior to the integer programming approach and the Lagrangian relaxation method.

Suggested Citation

  • Weiwei Chen & Liang Pi & Leyuan Shi, 2009. "Nested Partitions and Its Applications to the Intermodal Hub Location Problem," Springer Optimization and Its Applications, in: Wanpracha Chaovalitwongse & Kevin C. Furman & Panos M. Pardalos (ed.), Optimization and Logistics Challenges in the Enterprise, pages 229-251, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-88617-6_8
    DOI: 10.1007/978-0-387-88617-6_8
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    Cited by:

    1. Hao Howard Zhang & Leyuan Shi & Robert Meyer & Daryl Nazareth & Warren D'Souza, 2009. "Solving Beam-Angle Selection and Dose Optimization Simultaneously via High-Throughput Computing," INFORMS Journal on Computing, INFORMS, vol. 21(3), pages 427-444, August.
    2. Choi, Hyunhong & Koo, Yoonmo, 2018. "Using Contingent Valuation and Numerical Methods to Determine Optimal Locations for Environmental Facilities: Public Arboretums in South Korea," Ecological Economics, Elsevier, vol. 149(C), pages 184-201.

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