A stochastic fleet composition problem

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 t...

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Main Authors: Loxton, Ryan, Lin, Qun, Teo, Kok Lay
Format: Journal Article
Published: ELSEVIER 2012
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/31771
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author Loxton, Ryan
Lin, Qun
Teo, Kok Lay
author_facet Loxton, Ryan
Lin, Qun
Teo, Kok Lay
author_sort Loxton, Ryan
building Curtin Institutional Repository
collection Online Access
description 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.
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institution Curtin University Malaysia
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publishDate 2012
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spelling curtin-20.500.11937-317712019-02-19T04:28:17Z A stochastic fleet composition problem Loxton, Ryan Lin, Qun Teo, Kok Lay Convex optimization Golden section method Fleet composition Dynamic programming 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. 2012 Journal Article http://hdl.handle.net/20.500.11937/31771 10.1016/j.cor.2012.04.004 ELSEVIER fulltext
spellingShingle Convex optimization
Golden section method
Fleet composition
Dynamic programming
Loxton, Ryan
Lin, Qun
Teo, Kok Lay
A stochastic fleet composition problem
title A stochastic fleet composition problem
title_full A stochastic fleet composition problem
title_fullStr A stochastic fleet composition problem
title_full_unstemmed A stochastic fleet composition problem
title_short A stochastic fleet composition problem
title_sort stochastic fleet composition problem
topic Convex optimization
Golden section method
Fleet composition
Dynamic programming
url http://hdl.handle.net/20.500.11937/31771