{"title":"基于混合跳跃基因遗传算法的多目标路由请求调度方法","authors":"M. Rahman, S. Mondol, G. S. Hossain, A. Dey","doi":"10.1109/ICICT.2007.375405","DOIUrl":null,"url":null,"abstract":"This paper presents a hybrid jumping genes genetic algorithm (HJGGA) for solving the request scheduling problem in multiple destination routing (MDR). The problem incorporates the scheduling and routing process of a set of requests having single source and multiple destinations through a network. Our proposed HJGGA framework, that facilitates intelligent splitting of bandwidth requirement of requests as well as multiple optimal paths for transmission, searches for a near-optimal scheduling solution. We have also developed new chromosome-encoding and mutation technique for our HJGGA. Experimental result shows that our scheme reflects better real world situations and performs superior than previous researches.","PeriodicalId":206443,"journal":{"name":"2007 International Conference on Information and Communication Technology","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Hybrid Jumping Genes Genetic Algorithm Based Request Scheduling Approach in Multiple Destination Routing\",\"authors\":\"M. Rahman, S. Mondol, G. S. Hossain, A. Dey\",\"doi\":\"10.1109/ICICT.2007.375405\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a hybrid jumping genes genetic algorithm (HJGGA) for solving the request scheduling problem in multiple destination routing (MDR). The problem incorporates the scheduling and routing process of a set of requests having single source and multiple destinations through a network. Our proposed HJGGA framework, that facilitates intelligent splitting of bandwidth requirement of requests as well as multiple optimal paths for transmission, searches for a near-optimal scheduling solution. We have also developed new chromosome-encoding and mutation technique for our HJGGA. Experimental result shows that our scheme reflects better real world situations and performs superior than previous researches.\",\"PeriodicalId\":206443,\"journal\":{\"name\":\"2007 International Conference on Information and Communication Technology\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Information and Communication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICT.2007.375405\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Information and Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICT.2007.375405","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Hybrid Jumping Genes Genetic Algorithm Based Request Scheduling Approach in Multiple Destination Routing
This paper presents a hybrid jumping genes genetic algorithm (HJGGA) for solving the request scheduling problem in multiple destination routing (MDR). The problem incorporates the scheduling and routing process of a set of requests having single source and multiple destinations through a network. Our proposed HJGGA framework, that facilitates intelligent splitting of bandwidth requirement of requests as well as multiple optimal paths for transmission, searches for a near-optimal scheduling solution. We have also developed new chromosome-encoding and mutation technique for our HJGGA. Experimental result shows that our scheme reflects better real world situations and performs superior than previous researches.