Technical Note-Worst-Case Benefit of Restocking for the Vehicle Routing Problem with Stochastic Demands

• 成果类型: Article
• 署名作者: Bertazzi, Luca; Secomandi, Nicola
• 署名单位: University of Brescia; Carnegie Mellon University
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2019.1901
• 发表日期: 2020
• 页码: 671-675
• 关键词: algorithms

摘要

The extant literature on the vehicle routing problem with stochastic demands indicates that the restocking strategy yields moderate percentage expected cost reductions relative to the a priori approach but lacks theoretical support for this improvement. We conduct a worst-case analysis that corroborates the observed restocking benefits and enhances our understanding of a foundational model in logistics under uncertainty.