{"title":"基于排序模糊数法的作业调度","authors":"Koun-Tem Sun","doi":"10.1109/KES.1998.725958","DOIUrl":null,"url":null,"abstract":"Proposes a fuzzy ranking method to solve job scheduling problems. The proposed fuzzy ranking method is based on the concept of the center of gravity method. For each job in a job scheduling problem, the profit is transferred into the membership value, and the deadline is transferred into the value of a fuzzy element X. Then, each job can be transferred into a fuzzy number, and we can find the centroid (center) of this fuzzy number by applying the proposed fuzzy ranking method. Based on these ranking values, a good job sequencing can be obtained. Simulation tests show that generated solutions by the ranking fuzzy number approach are better than by the traditional greedy algorithm for solving the complex job scheduling problems.","PeriodicalId":394492,"journal":{"name":"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Job scheduling using ranking fuzzy number method\",\"authors\":\"Koun-Tem Sun\",\"doi\":\"10.1109/KES.1998.725958\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Proposes a fuzzy ranking method to solve job scheduling problems. The proposed fuzzy ranking method is based on the concept of the center of gravity method. For each job in a job scheduling problem, the profit is transferred into the membership value, and the deadline is transferred into the value of a fuzzy element X. Then, each job can be transferred into a fuzzy number, and we can find the centroid (center) of this fuzzy number by applying the proposed fuzzy ranking method. Based on these ranking values, a good job sequencing can be obtained. Simulation tests show that generated solutions by the ranking fuzzy number approach are better than by the traditional greedy algorithm for solving the complex job scheduling problems.\",\"PeriodicalId\":394492,\"journal\":{\"name\":\"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KES.1998.725958\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KES.1998.725958","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Proposes a fuzzy ranking method to solve job scheduling problems. The proposed fuzzy ranking method is based on the concept of the center of gravity method. For each job in a job scheduling problem, the profit is transferred into the membership value, and the deadline is transferred into the value of a fuzzy element X. Then, each job can be transferred into a fuzzy number, and we can find the centroid (center) of this fuzzy number by applying the proposed fuzzy ranking method. Based on these ranking values, a good job sequencing can be obtained. Simulation tests show that generated solutions by the ranking fuzzy number approach are better than by the traditional greedy algorithm for solving the complex job scheduling problems.