{"title":"基于遗传算法的跨阶段逆向物流规划","authors":"Z. Che, T. Chiang, K. Hsiao, C. Chen, J. Chang","doi":"10.1145/3127942.3127944","DOIUrl":null,"url":null,"abstract":"The cross-stage reverse logistics planning is a key issue in the supply chain management. This paper emphasizes to propose a mathematical model for the cross-stage reverse logistics planning problem. We focus on the analysis on how to send the good products to the downstream supply chain partners for selling to the customer and the defective products back to the upstream supply chain partners for reprocessing based on the damage style. The capacity of each partner and the customer demand are considered in the planning process. Then, the genetic algorithm is employed for solving the mathematical model. Finally, the analytical result of an illustrative example is discussed to show the quality solution gained from the proposed mathematical model and solving method.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Cross-stage Reverse Logistics Planning via a Genetic Algorithm\",\"authors\":\"Z. Che, T. Chiang, K. Hsiao, C. Chen, J. Chang\",\"doi\":\"10.1145/3127942.3127944\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The cross-stage reverse logistics planning is a key issue in the supply chain management. This paper emphasizes to propose a mathematical model for the cross-stage reverse logistics planning problem. We focus on the analysis on how to send the good products to the downstream supply chain partners for selling to the customer and the defective products back to the upstream supply chain partners for reprocessing based on the damage style. The capacity of each partner and the customer demand are considered in the planning process. Then, the genetic algorithm is employed for solving the mathematical model. Finally, the analytical result of an illustrative example is discussed to show the quality solution gained from the proposed mathematical model and solving method.\",\"PeriodicalId\":270425,\"journal\":{\"name\":\"Proceedings of the 1st International Conference on Algorithms, Computing and Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st International Conference on Algorithms, Computing and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3127942.3127944\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3127942.3127944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cross-stage Reverse Logistics Planning via a Genetic Algorithm
The cross-stage reverse logistics planning is a key issue in the supply chain management. This paper emphasizes to propose a mathematical model for the cross-stage reverse logistics planning problem. We focus on the analysis on how to send the good products to the downstream supply chain partners for selling to the customer and the defective products back to the upstream supply chain partners for reprocessing based on the damage style. The capacity of each partner and the customer demand are considered in the planning process. Then, the genetic algorithm is employed for solving the mathematical model. Finally, the analytical result of an illustrative example is discussed to show the quality solution gained from the proposed mathematical model and solving method.