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dc.contributor.authorLoxton, Ryan
dc.contributor.authorLin, Qun
dc.contributor.authorTeo, Kok Lay
dc.identifier.citationLoxton, Ryan and Lin, Qun and Teo, Kok Lay. 2012. A stochastic fleet composition problem. Computers and Operations Research. 39 (12): pp. 3177-3184.

In this paper, we consider the problem of forming a new vehicle fleet, consisting of multiple vehicle types, to cater for uncertain future requirements. The problem is to choose the number of vehicles of each type to purchase so that the total expected cost of operating the fleet is minimized. The total expected cost includes fixed and variable costs associated with the fleet, as well as hiring costs that are incurred whenever vehicle requirements exceed fleet capacity. We develop a novel algorithm, which combines dynamic programming and the golden section method, for determining the optimal fleet composition. Numerical results show that this algorithm is highly effective, and takes just seconds to solve large-scale problems involving hundreds of different vehicle types.

dc.subjectConvex optimization
dc.subjectGolden section method
dc.subjectFleet composition
dc.subjectDynamic programming
dc.titleA stochastic fleet composition problem
dc.typeJournal Article
dcterms.source.titleComputers and Operations Research

NOTICE: This is the author’s version of a work that was accepted for publication in Computers and Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Operations Research, Vol. 39, Issue 12 (2012). doi: 10.1016/j.cor.2012.04.004

curtin.accessStatusOpen access

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