Abstract The fleet deployment problem is a tactical planning problem in the shipping industry that seeks to efficiently assign ships to predetermined shipping services to meet the uncertain and seasonal changing demands caused by a highly fluctuating market. Once the fleet deployment plan is fixed, the allocated capacity on each service affects the possible flows transported and the profit obtained. This paper proposes a two-stage robust optimization model for ship fleet deployment and shipping revenue management of a liner shipping network under demand uncertainty. The randomness of demand in our model is represented by probability-free uncertain sets. A column-and-constraint generation based exact algorithm is designed to solve our model based on the analysis of its structural properties. To further accelerate the convergence of our algorithm, an M -tightening technique has been exploited. Finally, extensive computational experiments based on realistic instances are conducted to validate the effectiveness of our model and the efficiency of the algorithm; further, managerial insights are acquired based on the numerical results.

    Highlights Consider ship fleet deployment in liner shipping with revenue management under uncertainty. Develop a two-stage robust optimization model. Develop a column-and-constraint generation based exact algorithm. Conduct extensive numerical experiments to test the model and algorithm.


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    Titel :

    Robust ship fleet deployment with shipping revenue management


    Beteiligte:
    Lai, Xiaofan (Autor:in) / Wu, Lingxiao (Autor:in) / Wang, Kai (Autor:in) / Wang, Fan (Autor:in)


    Erscheinungsdatum :

    2022-05-07


    Format / Umfang :

    28 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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