{"title":"供应商管理库存系统下的库存路由方法","authors":"A. Borade, S. Bansod","doi":"10.1504/IJSSCI.2010.035761","DOIUrl":null,"url":null,"abstract":"Vendor managed inventory is a collaborative business practice adopted by organisations to improve the business performance. Under this practice, the retailers share demand and other related information with the manufacturer, who in turn manages the inventory of the retailer. In such event, the manufacturer assumes the responsibility of taking the decisions about size and time of delivery, vehicle routing, etc. This study examines the vendor managed inventory practice, specifically inventory routing problem, for retailers and a manufacturer when there is a wide fluctuation of daily demand. We have addressed a special issue related to inventory replenishment in vendor managed inventory system, where demand exceeds the finite production capacity .We construct a numerical experiment in MATLAB to find the optimal daily demand distribution and vehicle routing using fuzzy min-max learning algorithm. First, for deciding the sequence in which the quantity to be delivered to the retailers, a fuzzy set hyperboxes are used .Then, assignment is done with the help of discounting coefficient. Lastly, routing is done using fuzzy iterative algorithm. The focus of this paper is on demonstrating the effectiveness of our approach and comparing the results with that of simple greedy heuristics.","PeriodicalId":365774,"journal":{"name":"International Journal of Services Sciences","volume":"71 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An approach for inventory routing under vendor managed inventory system\",\"authors\":\"A. Borade, S. Bansod\",\"doi\":\"10.1504/IJSSCI.2010.035761\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vendor managed inventory is a collaborative business practice adopted by organisations to improve the business performance. Under this practice, the retailers share demand and other related information with the manufacturer, who in turn manages the inventory of the retailer. In such event, the manufacturer assumes the responsibility of taking the decisions about size and time of delivery, vehicle routing, etc. This study examines the vendor managed inventory practice, specifically inventory routing problem, for retailers and a manufacturer when there is a wide fluctuation of daily demand. We have addressed a special issue related to inventory replenishment in vendor managed inventory system, where demand exceeds the finite production capacity .We construct a numerical experiment in MATLAB to find the optimal daily demand distribution and vehicle routing using fuzzy min-max learning algorithm. First, for deciding the sequence in which the quantity to be delivered to the retailers, a fuzzy set hyperboxes are used .Then, assignment is done with the help of discounting coefficient. Lastly, routing is done using fuzzy iterative algorithm. The focus of this paper is on demonstrating the effectiveness of our approach and comparing the results with that of simple greedy heuristics.\",\"PeriodicalId\":365774,\"journal\":{\"name\":\"International Journal of Services Sciences\",\"volume\":\"71 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Services Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJSSCI.2010.035761\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Services Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJSSCI.2010.035761","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An approach for inventory routing under vendor managed inventory system
Vendor managed inventory is a collaborative business practice adopted by organisations to improve the business performance. Under this practice, the retailers share demand and other related information with the manufacturer, who in turn manages the inventory of the retailer. In such event, the manufacturer assumes the responsibility of taking the decisions about size and time of delivery, vehicle routing, etc. This study examines the vendor managed inventory practice, specifically inventory routing problem, for retailers and a manufacturer when there is a wide fluctuation of daily demand. We have addressed a special issue related to inventory replenishment in vendor managed inventory system, where demand exceeds the finite production capacity .We construct a numerical experiment in MATLAB to find the optimal daily demand distribution and vehicle routing using fuzzy min-max learning algorithm. First, for deciding the sequence in which the quantity to be delivered to the retailers, a fuzzy set hyperboxes are used .Then, assignment is done with the help of discounting coefficient. Lastly, routing is done using fuzzy iterative algorithm. The focus of this paper is on demonstrating the effectiveness of our approach and comparing the results with that of simple greedy heuristics.