Bunker fuel cost and freight revenue optimization for a single liner shipping service

•We consider bunker fuel cost and freight revenue jointly and the optimization is more detailed and precise than other studies. Our study can provide specific strategy about sailing, bunkering and loading for a single shipping liner service.•In view of the nonlinearity of the original model, we give...

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Bibliographic Details
Published in:Computers & operations research 2019-11, Vol.111, p.67-83
Main Authors: Wang, Sainan, Gao, Suixiang, Tan, Tunzi, Yang, Wenguo
Format: Article
Language:English
Subjects:
Bunker fuel cost
Bunkering
Bunkers (fuel)
Feasibility studies
Freight revenue
Fuels
Integer programming
Integers
Linear programming
Liner shipping service
Mathematical programming
Nonlinear programming
Operations research
Optimization
Production scheduling
Revenue
Sailing
Sailing speed
Shipment
Shipping
Shipping industry
Upper bounds
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Summary:•We consider bunker fuel cost and freight revenue jointly and the optimization is more detailed and precise than other studies. Our study can provide specific strategy about sailing, bunkering and loading for a single shipping liner service.•In view of the nonlinearity of the original model, we give a mixed-integer linear programming model and prove that it can provide feasible solutions for the original nonlinear model.•The case study demonstrates our model can indeed obtain good quality solutions. This paper aims to maximize the freight revenue minus bunker fuel cost for a single liner shipping service. This optimization contains the determination of the sailing speeds, bunkering strategy, and shipment strategy. We first formulate this optimization problem as a mixed-integer nonlinear programming model and then make some transformations to linearize the nonlinear terms. The transformed model is a mixed-integer linear programming model and provides an upper bound for the original model. We then construct another mixed-integer linear programming model and prove that its any optimal solution can be transformed into a feasible solution of the original model. In case studies, the proposed models are applied to two real liner service routes and the computational results demonstrate the efficiency and effectiveness of our solution method. Some insights from numerical experiments are provided in the end.
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2019.06.003