{"title":"An Approach for Earliness and Tardiness Scheduling Problems of Flow Shop with Uncertainty","authors":"Zhenhao Xu, Xingsheng Gu","doi":"10.1109/WCICA.2006.1714507","DOIUrl":null,"url":null,"abstract":"There are various uncertainties in the production scheduling of industrial processes in reality. The earliness/tardiness flow shop scheduling problems under uncertainty with different due windows are discussed in the paper. Based on the fuzzy programming theory, a scheduling model has been established and the uncertain processing time can be dealt with by fuzzy mathematics. And a fuzzy scheduling algorithm is proposed by analogy with the concept and the principle of biological immune system. Simulation results demonstrate the effectiveness of the fuzzy scheduling model and the better astringency of the algorithm","PeriodicalId":375135,"journal":{"name":"2006 6th World Congress on Intelligent Control and Automation","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 6th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2006.1714507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
There are various uncertainties in the production scheduling of industrial processes in reality. The earliness/tardiness flow shop scheduling problems under uncertainty with different due windows are discussed in the paper. Based on the fuzzy programming theory, a scheduling model has been established and the uncertain processing time can be dealt with by fuzzy mathematics. And a fuzzy scheduling algorithm is proposed by analogy with the concept and the principle of biological immune system. Simulation results demonstrate the effectiveness of the fuzzy scheduling model and the better astringency of the algorithm
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