{"title":"连续遗传算法在由订单到库存策略控制的物流网络优化中的应用","authors":"P. Ignaciuk","doi":"10.17781/P002312","DOIUrl":null,"url":null,"abstract":"The paper addresses the optimization problem of goods distribution process in logistic networks. The controlled nodes in the considered class of networks form a mesh structure. The stock level at the nodes is replenished from external sources and other nodes in the controlled network. The external demand is imposed on any node without prior knowledge about the requested quantity. Inventory control is realized through the application of order-up-to policy implemented in a distributed way. The aim is to provide high customer satisfaction while minimizing the total holding costs. In order to determine the optimal reference stock level for the policy operation a continuous genetic algorithm is applied and adjusted for the analyzed class of application centered problems.","PeriodicalId":211757,"journal":{"name":"International journal of new computer architectures and their applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Application of Continuous Genetic Algorithms for Optimization of Logistic Networks Governed by Order-Up-To Inventory Policy\",\"authors\":\"P. Ignaciuk\",\"doi\":\"10.17781/P002312\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper addresses the optimization problem of goods distribution process in logistic networks. The controlled nodes in the considered class of networks form a mesh structure. The stock level at the nodes is replenished from external sources and other nodes in the controlled network. The external demand is imposed on any node without prior knowledge about the requested quantity. Inventory control is realized through the application of order-up-to policy implemented in a distributed way. The aim is to provide high customer satisfaction while minimizing the total holding costs. In order to determine the optimal reference stock level for the policy operation a continuous genetic algorithm is applied and adjusted for the analyzed class of application centered problems.\",\"PeriodicalId\":211757,\"journal\":{\"name\":\"International journal of new computer architectures and their applications\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of new computer architectures and their applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17781/P002312\",\"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 new computer architectures and their applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17781/P002312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Continuous Genetic Algorithms for Optimization of Logistic Networks Governed by Order-Up-To Inventory Policy
The paper addresses the optimization problem of goods distribution process in logistic networks. The controlled nodes in the considered class of networks form a mesh structure. The stock level at the nodes is replenished from external sources and other nodes in the controlled network. The external demand is imposed on any node without prior knowledge about the requested quantity. Inventory control is realized through the application of order-up-to policy implemented in a distributed way. The aim is to provide high customer satisfaction while minimizing the total holding costs. In order to determine the optimal reference stock level for the policy operation a continuous genetic algorithm is applied and adjusted for the analyzed class of application centered problems.