{"title":"针对货架空间分配问题调整了网络流量","authors":"A. Lim, B. Rodrigues, Fei Xiao, Xingwen Zhang","doi":"10.1109/TAI.2002.1180808","DOIUrl":null,"url":null,"abstract":"In this paper, we study shelf space allocation optimization which is important to retail operations management. Our approach is to formulate a model that is applicable to operational realities and to seek solutions with realistic test data. This model is linked to the multidimensional knapsack problem. We first solve a simplified version of the problem to achieve maximum profit by transforming it into a network flow problem. Then, with simple adaptations we solve the general shelf space allocation problem with the help of the network flow model. The approach is simple and direct while experimental results improve on recent findings significantly and are very close to the optimal.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Adjusted network flow for the shelf-space allocation problem\",\"authors\":\"A. Lim, B. Rodrigues, Fei Xiao, Xingwen Zhang\",\"doi\":\"10.1109/TAI.2002.1180808\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we study shelf space allocation optimization which is important to retail operations management. Our approach is to formulate a model that is applicable to operational realities and to seek solutions with realistic test data. This model is linked to the multidimensional knapsack problem. We first solve a simplified version of the problem to achieve maximum profit by transforming it into a network flow problem. Then, with simple adaptations we solve the general shelf space allocation problem with the help of the network flow model. The approach is simple and direct while experimental results improve on recent findings significantly and are very close to the optimal.\",\"PeriodicalId\":197064,\"journal\":{\"name\":\"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.2002.1180808\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.2002.1180808","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adjusted network flow for the shelf-space allocation problem
In this paper, we study shelf space allocation optimization which is important to retail operations management. Our approach is to formulate a model that is applicable to operational realities and to seek solutions with realistic test data. This model is linked to the multidimensional knapsack problem. We first solve a simplified version of the problem to achieve maximum profit by transforming it into a network flow problem. Then, with simple adaptations we solve the general shelf space allocation problem with the help of the network flow model. The approach is simple and direct while experimental results improve on recent findings significantly and are very close to the optimal.