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Bi-criteria approach to containership slot allocation in liner shipping

Author

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  • Shih-Chan Ting

    (Faculty of Maritime Transport and Management, Department of Transportation Science, National Taiwan Ocean University, No. 2, Pei-Ning Road, Keelung, Taiwan)

  • Gwo-Hshiung Tzeng

    (Graduate Institute of Urban Planning, National Taipei University, 151, University Rd., San Shia District, New Taipei City, Taiwan)

Abstract

Containership capacity allocation is an important issue since liner companies must avoid unused space on a voyage to maximize their revenue. Therefore, in the face of uncertain cargo demand and fiercely competitive markets, liner carriers build revenue management systems to maximize voyage profits through careful consideration of slot allocation and pricing. A containership slot allocation model is proposed in this article to deal with two conflicting objectives: carrier’s freight contribution and agents’ degree of satisfaction, as well as fuzzy constraints, that is, uncertainties of cargo transportation demand and weight. This model is formulated using fuzzy multi-objective programming for deep-sea liner service containership slot allocation. Interactive fuzzy multi-objective linear programming with fuzzy parameters is applied to solve this problem. The proposed model is applied to an Asia-Europe service route of a liner company to test its efficacy. Results show the model’s applicability and excellent performance in practice.

Suggested Citation

  • Shih-Chan Ting & Gwo-Hshiung Tzeng, 2016. "Bi-criteria approach to containership slot allocation in liner shipping," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 18(2), pages 141-157, June.
    • Handle: RePEc:pal:marecl:v:18:y:2016:i:2:p:141-157
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    Cited by:

    1. Wang, Tingsong & Meng, Qiang & Wang, Shuaian & Qu, Xiaobo, 2021. "A two-stage stochastic nonlinear integer-programming model for slot allocation of a liner container shipping service," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 143-160.

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