{"title":"血液制品的综合库存和分配计划问题:土耳其红新月会的申请","authors":"Atıl Kurt, M. Azizoglu, F. C. Çetinkaya","doi":"10.5267/j.dsl.2023.1.004","DOIUrl":null,"url":null,"abstract":"This study considers an integrated inventory planning and distribution problem based on an applied case at the Turkish Red Crescent’s Central Anatolian Regional Blood Center. We define two echelons, the first echelon being the regional blood center and the second echelon being the districts. The blood products are perishable so that the outdated products are disposed of at the end of their lives. We aim to minimize the cost of inventory keeping at both echelons, the shortage, and disposal amounts at the second echelon. We consider two distribution strategies: all deliveries are realized by the regional blood center (current implementation), and the deliveries are directly from the regional blood center or the other districts. We develop a mixed-integer linear programming model for each strategy. Our experimental results show that the decentralized strategy brings significant cost reductions over the centralized strategy. The mathematical model for the centralized distribution strategy can handle large-sized instances. On the other hand, the model for the decentralized distribution strategy is more complex and could not handle large-sized instances in our pre-specified termination limit of two hours. For large-sized instances of the decentralized distribution strategy, we design a decomposition-based heuristic algorithm that benefits from the optimal solutions of the original model and finds near-optimal solutions very quickly.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An integrated inventory and distribution planning problem for the blood products: An application for the Turkish Red Crescent\",\"authors\":\"Atıl Kurt, M. Azizoglu, F. C. Çetinkaya\",\"doi\":\"10.5267/j.dsl.2023.1.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study considers an integrated inventory planning and distribution problem based on an applied case at the Turkish Red Crescent’s Central Anatolian Regional Blood Center. We define two echelons, the first echelon being the regional blood center and the second echelon being the districts. The blood products are perishable so that the outdated products are disposed of at the end of their lives. We aim to minimize the cost of inventory keeping at both echelons, the shortage, and disposal amounts at the second echelon. We consider two distribution strategies: all deliveries are realized by the regional blood center (current implementation), and the deliveries are directly from the regional blood center or the other districts. We develop a mixed-integer linear programming model for each strategy. Our experimental results show that the decentralized strategy brings significant cost reductions over the centralized strategy. The mathematical model for the centralized distribution strategy can handle large-sized instances. On the other hand, the model for the decentralized distribution strategy is more complex and could not handle large-sized instances in our pre-specified termination limit of two hours. For large-sized instances of the decentralized distribution strategy, we design a decomposition-based heuristic algorithm that benefits from the optimal solutions of the original model and finds near-optimal solutions very quickly.\",\"PeriodicalId\":38141,\"journal\":{\"name\":\"Decision Science Letters\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Decision Science Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5267/j.dsl.2023.1.004\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decision Science Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5267/j.dsl.2023.1.004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
An integrated inventory and distribution planning problem for the blood products: An application for the Turkish Red Crescent
This study considers an integrated inventory planning and distribution problem based on an applied case at the Turkish Red Crescent’s Central Anatolian Regional Blood Center. We define two echelons, the first echelon being the regional blood center and the second echelon being the districts. The blood products are perishable so that the outdated products are disposed of at the end of their lives. We aim to minimize the cost of inventory keeping at both echelons, the shortage, and disposal amounts at the second echelon. We consider two distribution strategies: all deliveries are realized by the regional blood center (current implementation), and the deliveries are directly from the regional blood center or the other districts. We develop a mixed-integer linear programming model for each strategy. Our experimental results show that the decentralized strategy brings significant cost reductions over the centralized strategy. The mathematical model for the centralized distribution strategy can handle large-sized instances. On the other hand, the model for the decentralized distribution strategy is more complex and could not handle large-sized instances in our pre-specified termination limit of two hours. For large-sized instances of the decentralized distribution strategy, we design a decomposition-based heuristic algorithm that benefits from the optimal solutions of the original model and finds near-optimal solutions very quickly.