{"title":"Vehicle dispatching policies for last mile distribution in a disaster-relief supply chain network","authors":"Robert A. Cook, Emmett J. Lodree","doi":"10.1007/s10479-025-06756-9","DOIUrl":null,"url":null,"abstract":"<div><p>This study considers the impact of supply and demand uncertainty on last-mile distribution in a disaster-relief supply chain with multiple Staging Areas (SAs) and one Point of Distribution (POD). The SAs function as temporary warehouses for receiving and organizing relief supplies that are subsequently transported to the POD where they are distributed to meet the stochastic demands of disaster survivors. The goal of this paper is to evaluate the effectiveness of policies for dispatching vehicles from the SAs to the POD in an effort to minimize unsatisfied demand at the POD. Prior literature suggests that continuously dispatching vehicles is an effective and pragmatic policy, but it has not been tested on a relief network with multiple Staging Areas. This study establishes criteria under which continuous dispatching (CD) is an optimal policy and examines its performance through computational experiments. We solve problem instances using approximate dynamic programming since the stochastic dynamic programming model cannot be solved directly. Our findings suggest that the CD policy does not perform as well as in previous studies, but may be the best available option from a practical perspective.</p></div>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"352 1-2","pages":"25 - 73"},"PeriodicalIF":4.5000,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Operations Research","FirstCategoryId":"91","ListUrlMain":"https://link.springer.com/article/10.1007/s10479-025-06756-9","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This study considers the impact of supply and demand uncertainty on last-mile distribution in a disaster-relief supply chain with multiple Staging Areas (SAs) and one Point of Distribution (POD). The SAs function as temporary warehouses for receiving and organizing relief supplies that are subsequently transported to the POD where they are distributed to meet the stochastic demands of disaster survivors. The goal of this paper is to evaluate the effectiveness of policies for dispatching vehicles from the SAs to the POD in an effort to minimize unsatisfied demand at the POD. Prior literature suggests that continuously dispatching vehicles is an effective and pragmatic policy, but it has not been tested on a relief network with multiple Staging Areas. This study establishes criteria under which continuous dispatching (CD) is an optimal policy and examines its performance through computational experiments. We solve problem instances using approximate dynamic programming since the stochastic dynamic programming model cannot be solved directly. Our findings suggest that the CD policy does not perform as well as in previous studies, but may be the best available option from a practical perspective.
期刊介绍:
The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications.
In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.