{"title":"基于蚁群优化的供应链动态调度方法研究","authors":"Wang Xu, Jia Yan-min, Yu Tian-lai","doi":"10.1109/INDIN.2008.4618216","DOIUrl":null,"url":null,"abstract":"In order to improve the efficiency of supply chain dynamic scheduling, according to the essential operation characteristics and mechanism in supply chain dynamic scheduling, dynamic scheduling operation method in supply chain was studied through ant colony optimization algorithm. The supply chain dynamic scheduling based on ant colony optimization algorithm was simulated by experimental data. When generation iteration is 500 times, the power trend curve of optimal evaluation index is convergence in 115.156. The optimal scheme appears in generation 365. All orders are completed within constraint units. The production cost and the inventory cost are minimums. By comparison confirmed, the method has better optimal performance and adaptability. Dynamic scheduling operation method based on ant colony optimization is better than that of genetic algorithm and expert systems.","PeriodicalId":112553,"journal":{"name":"2008 6th IEEE International Conference on Industrial Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Research on dynamic scheduling operation method in supply chain based on Ant Colony Optimization\",\"authors\":\"Wang Xu, Jia Yan-min, Yu Tian-lai\",\"doi\":\"10.1109/INDIN.2008.4618216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the efficiency of supply chain dynamic scheduling, according to the essential operation characteristics and mechanism in supply chain dynamic scheduling, dynamic scheduling operation method in supply chain was studied through ant colony optimization algorithm. The supply chain dynamic scheduling based on ant colony optimization algorithm was simulated by experimental data. When generation iteration is 500 times, the power trend curve of optimal evaluation index is convergence in 115.156. The optimal scheme appears in generation 365. All orders are completed within constraint units. The production cost and the inventory cost are minimums. By comparison confirmed, the method has better optimal performance and adaptability. Dynamic scheduling operation method based on ant colony optimization is better than that of genetic algorithm and expert systems.\",\"PeriodicalId\":112553,\"journal\":{\"name\":\"2008 6th IEEE International Conference on Industrial Informatics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 6th IEEE International Conference on Industrial Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDIN.2008.4618216\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 6th IEEE International Conference on Industrial Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN.2008.4618216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on dynamic scheduling operation method in supply chain based on Ant Colony Optimization
In order to improve the efficiency of supply chain dynamic scheduling, according to the essential operation characteristics and mechanism in supply chain dynamic scheduling, dynamic scheduling operation method in supply chain was studied through ant colony optimization algorithm. The supply chain dynamic scheduling based on ant colony optimization algorithm was simulated by experimental data. When generation iteration is 500 times, the power trend curve of optimal evaluation index is convergence in 115.156. The optimal scheme appears in generation 365. All orders are completed within constraint units. The production cost and the inventory cost are minimums. By comparison confirmed, the method has better optimal performance and adaptability. Dynamic scheduling operation method based on ant colony optimization is better than that of genetic algorithm and expert systems.
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