{"title":"基于多智能体制造网格的资源调度新研究","authors":"Qiao Lu, Ning Song, Shibing Zhou","doi":"10.1109/APWCS.2010.110","DOIUrl":null,"url":null,"abstract":"According to the complex environment of wide-area, dynamic and heterogeneous in the manufacturing grid, how quickly and accurately discover and the schedule resources, enable QoS to achieve the desired effect, this paper presented the new method to discovering the resources of using Mobile Agent in the manufacturing grid, has designed the resources optimal goal, improved genetic ant colony algorithm way optimization strategy, might obtain the very good convergence speed and exact solutions after the simulation experiment certificate.","PeriodicalId":354322,"journal":{"name":"2010 Asia-Pacific Conference on Wearable Computing Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Research of Resource Scheduling Based on Multi-agent Manufacturing Grid\",\"authors\":\"Qiao Lu, Ning Song, Shibing Zhou\",\"doi\":\"10.1109/APWCS.2010.110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"According to the complex environment of wide-area, dynamic and heterogeneous in the manufacturing grid, how quickly and accurately discover and the schedule resources, enable QoS to achieve the desired effect, this paper presented the new method to discovering the resources of using Mobile Agent in the manufacturing grid, has designed the resources optimal goal, improved genetic ant colony algorithm way optimization strategy, might obtain the very good convergence speed and exact solutions after the simulation experiment certificate.\",\"PeriodicalId\":354322,\"journal\":{\"name\":\"2010 Asia-Pacific Conference on Wearable Computing Systems\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Asia-Pacific Conference on Wearable Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APWCS.2010.110\",\"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 Asia-Pacific Conference on Wearable Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APWCS.2010.110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Research of Resource Scheduling Based on Multi-agent Manufacturing Grid
According to the complex environment of wide-area, dynamic and heterogeneous in the manufacturing grid, how quickly and accurately discover and the schedule resources, enable QoS to achieve the desired effect, this paper presented the new method to discovering the resources of using Mobile Agent in the manufacturing grid, has designed the resources optimal goal, improved genetic ant colony algorithm way optimization strategy, might obtain the very good convergence speed and exact solutions after the simulation experiment certificate.
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