Robust optimization for fleet planning under uncertainty

We create a formulation and a solution procedure for fleet sizing under uncertainty in future demands and operating conditions. The formulation focuses on robust optimization, using a partial moment measure of risk. This risk measure is incorporated into the expected recourse function of a two-stage...

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Bibliographic Details
Published in:Transportation research. Part E, Logistics and transportation review Logistics and transportation review, 2003-05, Vol.39 (3), p.209-227
Main Authors: List, George F, Wood, Bryan, Nozick, Linda K, Turnquist, Mark A, Jones, Dean A, Kjeldgaard, Edwin A, Lawton, Craig R
Format: Article
Language:English
Subjects:
Fleet sizing
Logistics
Mathematical models
Optimization
Robust optimization
Stochastic decomposition
Stochastic optimization
Stochastic optimization Fleet sizing Stochastic decomposition Robust optimization
Studies
Transportation economics
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Summary:We create a formulation and a solution procedure for fleet sizing under uncertainty in future demands and operating conditions. The formulation focuses on robust optimization, using a partial moment measure of risk. This risk measure is incorporated into the expected recourse function of a two-stage stochastic programming formulation, and stochastic decomposition is used as a solution procedure. A numerical example illustrates the importance of including uncertainty in the fleet sizing problem formulation, and the nature of the fundamental tradeoff between acquiring more vehicles and accepting the risk of potentially high costs if insufficient resources are available.
ISSN:1366-5545
1878-5794
DOI:10.1016/S1366-5545(02)00026-1