Fleet deployment in liner shipping with incomplete demand information

Man Wo Ng; Dung Ying Lin

doi:10.1016/j.tre.2018.06.004

Fleet deployment in liner shipping with incomplete demand information

Man Wo Ng
, Dung Ying Lin

Department of Transportation and Communication Management Science

Research output: Contribution to journal › Article › peer-review

26 Citations (Scopus)

Abstract

This paper examines the liner fleet deployment problem when only conditional shipping demand information is known. For such a case, it is generally not possible to determine the exact optimal solution. A set of complementary upper and lower bounds on the optimal cost are derived by exploiting the problem structure. These bounds are explicitly shown to converge to the optimal cost when a sufficiently refined partition is available. A numerical example illustrates the model.

Original language	English
Pages (from-to)	184-189
Number of pages	6
Journal	Transportation Research Part E: Logistics and Transportation Review
Volume	116
DOIs	https://doi.org/10.1016/j.tre.2018.06.004
Publication status	Published - 2018 Aug

All Science Journal Classification (ASJC) codes

Business and International Management
Civil and Structural Engineering
Transportation

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10.1016/j.tre.2018.06.004

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note = "Funding Information: The second author acknowledges the Ministry of Science and Technology, Taiwan, ROC, for providing partial funding support under contract number MOST 105-2628-H-006-003-MY3. The contents of the article remain the sole responsibility of the authors. Publisher Copyright: {\textcopyright} 2018 Elsevier Ltd",

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AB - This paper examines the liner fleet deployment problem when only conditional shipping demand information is known. For such a case, it is generally not possible to determine the exact optimal solution. A set of complementary upper and lower bounds on the optimal cost are derived by exploiting the problem structure. These bounds are explicitly shown to converge to the optimal cost when a sufficiently refined partition is available. A numerical example illustrates the model.

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JO - Transportation Research Part E: Logistics and Transportation Review

JF - Transportation Research Part E: Logistics and Transportation Review

ER -

Fleet deployment in liner shipping with incomplete demand information

Abstract

All Science Journal Classification (ASJC) codes

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