2003
DOI: 10.1016/s1366-5545(02)00026-1
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Robust optimization for fleet planning under uncertainty

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Cited by 133 publications
(70 citation statements)
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References 26 publications
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“…But vehicle routing times and vehicle loads are treated probabilistically by the authors. List et al (2003) study the fleet sizing problem under uncertainty assumptions over the demands, travel times, and availability of the vehicles. They propose a stochastic programming formulation and use the stochastic decomposition to solve it.…”
Section: Stochastic Fleet Sizing Problem Independent Of Vrp and Of Rementioning
confidence: 99%
“…But vehicle routing times and vehicle loads are treated probabilistically by the authors. List et al (2003) study the fleet sizing problem under uncertainty assumptions over the demands, travel times, and availability of the vehicles. They propose a stochastic programming formulation and use the stochastic decomposition to solve it.…”
Section: Stochastic Fleet Sizing Problem Independent Of Vrp and Of Rementioning
confidence: 99%
“…In [List et al, 2003], the authors analyze the performance of their algorithms in terms of robustness. According to them, the robustness is the ability of the algorithm to avoid extreme consequences on some scenarios, (as discussed in section 5.3).…”
Section: Mean and Variance Trade-offsmentioning
confidence: 99%
“…Percentage to the a-posteriori solution or bounds cited in [Spivey & Powell, 2004] 5. Mean and variance trade-offs cited in [List et al, 2003] 6. Statistical pairwise comparison test cited in [Tjokroamidjojo et al, 2006] These tests are described in the following sections.…”
Section: Introductionmentioning
confidence: 99%
“…A mathematical model and four different heuristics for direct deliveries are presented, and Some extensions to deal with the multiple-retailer-route situation are also proposed. List et al [93] developed a formulation and solution procedure for fleet sizing in a transportation network with uncertainty in demand and operating conditions. The formulation focuses on robust optimization and incorporates the risk into the expected recourse function of a two-stage stochastic programming formulation.…”
Section: Fleet Composition In Network Optimization Problemsmentioning
confidence: 99%