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Bunker Procurement Planning for Container Liner Shipping Companies

Multistage Stochastic Programming Approach
Authors: Qiang Meng; Yadong Wang; Yuquan Du;

Bunker Procurement Planning for Container Liner Shipping Companies

Abstract

This paper investigates the bunker procurement planning (BPP) problem arising for a container liner shipping company that plans to purchase bunker from both bunker futures contracts and the spot market to hedge the risk in fluctuation of and increases in bunker prices. A multistage bunker procurement decision process for the BPP problem is developed to determine the monthly bunker procurement. The process allows the shipping company to sign bunker futures contracts in the first stage and to rebalance them in the subsequent stages. By assuming the stochasticity of bunker spot price, the BPP problem is formulated as a mean-variance minimization stochastic programming model. An approximation solution method for solving this model is designed by integrating random variable sampling technique, scenario tree generation, and quadratic programming approximation. Finally, numerical experiments demonstrate that bunker procurement risk can be effectively hedged with the proposed method. This study provides a useful decision tool for container liner shipping companies to use when planning bunker procurement.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Average
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