Robust ship fleet deployment with shipping revenue management

Xiaofan Lai, Lingxiao Wu, Kai Wang and Fan Wang

Transportation Research Part B: Methodological, 2022, vol. 161, issue C, 169-196

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.

Keywords: Liner shipping; Ship fleet deployment; Shipping revenue management; Robust optimization (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.trb.2022.05.005

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