{"title":"柔性作业车间调度问题的免疫遗传算法","authors":"Jia Ma, Yunlong Zhu, Gang Shi","doi":"10.1109/ICAL.2010.5585331","DOIUrl":null,"url":null,"abstract":"An kind of immune genetic algorithm(IGA) is proposed for solving the flexible job-shop scheduling problem(FJSP). Based on the globalsearching method of classic genetic algorithm (SG), and using the diversity preservation strategy of antibodies in biology immunity mechanism, the method greatly improves the colony diversity of GA and compared to genetic algorithm. The results show that immune genetic algorithm performs better in aspect of global and local search ability and search speed.","PeriodicalId":393739,"journal":{"name":"2010 IEEE International Conference on Automation and Logistics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Immune genetic algorithm for flexible job-shop scheduling problem\",\"authors\":\"Jia Ma, Yunlong Zhu, Gang Shi\",\"doi\":\"10.1109/ICAL.2010.5585331\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An kind of immune genetic algorithm(IGA) is proposed for solving the flexible job-shop scheduling problem(FJSP). Based on the globalsearching method of classic genetic algorithm (SG), and using the diversity preservation strategy of antibodies in biology immunity mechanism, the method greatly improves the colony diversity of GA and compared to genetic algorithm. The results show that immune genetic algorithm performs better in aspect of global and local search ability and search speed.\",\"PeriodicalId\":393739,\"journal\":{\"name\":\"2010 IEEE International Conference on Automation and Logistics\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Automation and Logistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAL.2010.5585331\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Automation and Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAL.2010.5585331","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Immune genetic algorithm for flexible job-shop scheduling problem
An kind of immune genetic algorithm(IGA) is proposed for solving the flexible job-shop scheduling problem(FJSP). Based on the globalsearching method of classic genetic algorithm (SG), and using the diversity preservation strategy of antibodies in biology immunity mechanism, the method greatly improves the colony diversity of GA and compared to genetic algorithm. The results show that immune genetic algorithm performs better in aspect of global and local search ability and search speed.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
