{"title":"Solution Algorithm for The Multi-period Inventory Transshipment Problem Considering Rentals and Returns","authors":"Keiya Kadota, Tetsuya Sato, T. Shiina","doi":"10.1109/iiai-aai53430.2021.00151","DOIUrl":null,"url":null,"abstract":"Supply chain management is a large-scale planning under uncertainty. It is significant that building an efficient supply chain under uncertain conditions is a challenge. There are numerous traditional inventory transshipment models targeting only demands but do not include rentals and returns. This study provides the uncertainty between rentals and returns by scenarios using a multi-period stochastic programming model of inventory transshipment problems. The moment matching method was used to reduce the number of scenarios, and the comparative experiment demonstrated the utility of this model.","PeriodicalId":414070,"journal":{"name":"2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iiai-aai53430.2021.00151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Supply chain management is a large-scale planning under uncertainty. It is significant that building an efficient supply chain under uncertain conditions is a challenge. There are numerous traditional inventory transshipment models targeting only demands but do not include rentals and returns. This study provides the uncertainty between rentals and returns by scenarios using a multi-period stochastic programming model of inventory transshipment problems. The moment matching method was used to reduce the number of scenarios, and the comparative experiment demonstrated the utility of this model.