The Inventory Routing Problem Under Uncertainty

• 成果类型: Article
• 署名作者: Cui, Zheng; Long, Daniel Zhuoyu; Qi, Jin; Zhang, Lianmin
• 署名单位: Zhejiang University; Chinese University of Hong Kong; Hong Kong University of Science & Technology; Nanjing University; Shenzhen Research Institute of Big Data
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2022.2407
• 发表日期: 2023
• 页码: 378-395
• 关键词: distributionally robust optimization; Decision rules; MODEL; price; RISK; ADAPTABILITY; COORDINATION; heuristics; allocation; algorithm

摘要

We study an uncertain inventory routing problem with a finite horizon. The supplier acts as a central planner who determines the replenishment quantities and also, the delivery times and routes to all retailers. We allow ambiguity in the probability distribution of each retailer's uncertain demand. Adopting a service-level viewpoint, we minimize the risk of uncertain inventory levels violating a prespecified acceptable range. We quantify that risk using a novel decision criterion, the service violation index, that accounts for how often and how severely the inventory requirement is violated. The solutions proposed here are adaptive in that they vary with the realization of uncertain demand. We provide algorithms to solve the problem exactly and then, demonstrate the superiority of our solutions by comparing them with several benchmarks.