{"title":"Optimization of green agri-food supply chain network using chaotic PSO algorithm","authors":"Q. Tao, Zhexue Huang, Chunqin Gu, Chenxin Zhang","doi":"10.1109/SOLI.2013.6611459","DOIUrl":null,"url":null,"abstract":"In this paper, a chaotic Particle Swarm Optimization (CPSO) algorithm is presented to solve the green agri-food supply chain network (GASCN). The GASCN design is critical to reduce the total transportation cost for efficient and effective supply chain management. The traditional supply chain does not adequately satisfy the expectance of all the customers, therefore new model of supply chain of great urgency to be exploited. The main contribution of this paper is to find an optimal solution for GASCN problem and propose a new solution based on CPSO to optimize the GASCN. To show the efficacy of the CPSO algorithm, the algorithm is tested on three cases. Results show better performance of the CPSO in GASCN by both optimization speed and solution quality as compared to GA and CGA, especially when the scale of problem is large.","PeriodicalId":147180,"journal":{"name":"Proceedings of 2013 IEEE International Conference on Service Operations and Logistics, and Informatics","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2013 IEEE International Conference on Service Operations and Logistics, and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOLI.2013.6611459","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper, a chaotic Particle Swarm Optimization (CPSO) algorithm is presented to solve the green agri-food supply chain network (GASCN). The GASCN design is critical to reduce the total transportation cost for efficient and effective supply chain management. The traditional supply chain does not adequately satisfy the expectance of all the customers, therefore new model of supply chain of great urgency to be exploited. The main contribution of this paper is to find an optimal solution for GASCN problem and propose a new solution based on CPSO to optimize the GASCN. To show the efficacy of the CPSO algorithm, the algorithm is tested on three cases. Results show better performance of the CPSO in GASCN by both optimization speed and solution quality as compared to GA and CGA, especially when the scale of problem is large.