{"title":"具有模糊目标函数的线性规划","authors":"I. Alolyan","doi":"10.1109/ITNG.2013.123","DOIUrl":null,"url":null,"abstract":"The conventional Linear Programming (LP) model requires the parameters to be known as constants. In the real world, however, the parameters are seldom known exactly and have to be estimated. Interval programming is one of the tools to tackle uncertainty in mathematical programming models. In this paper, we consider LP problem whose coefficients are uncertain. The relations between closed and bounded intervals is derived, and the solution of such a problem is proposed by considering the partial orderings on the set of all closed intervals.","PeriodicalId":320262,"journal":{"name":"2013 10th International Conference on Information Technology: New Generations","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Linear Programming with Fuzzy Objective Function\",\"authors\":\"I. Alolyan\",\"doi\":\"10.1109/ITNG.2013.123\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The conventional Linear Programming (LP) model requires the parameters to be known as constants. In the real world, however, the parameters are seldom known exactly and have to be estimated. Interval programming is one of the tools to tackle uncertainty in mathematical programming models. In this paper, we consider LP problem whose coefficients are uncertain. The relations between closed and bounded intervals is derived, and the solution of such a problem is proposed by considering the partial orderings on the set of all closed intervals.\",\"PeriodicalId\":320262,\"journal\":{\"name\":\"2013 10th International Conference on Information Technology: New Generations\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 10th International Conference on Information Technology: New Generations\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITNG.2013.123\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th International Conference on Information Technology: New Generations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITNG.2013.123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The conventional Linear Programming (LP) model requires the parameters to be known as constants. In the real world, however, the parameters are seldom known exactly and have to be estimated. Interval programming is one of the tools to tackle uncertainty in mathematical programming models. In this paper, we consider LP problem whose coefficients are uncertain. The relations between closed and bounded intervals is derived, and the solution of such a problem is proposed by considering the partial orderings on the set of all closed intervals.
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