{"title":"An artificial variable RZ decision method for geometric superfluity of condition constraint in linear programming problem","authors":"Dao-jian Liu, Tian-min Huang","doi":"10.1109/ISKE.2010.5680794","DOIUrl":null,"url":null,"abstract":"In this paper, based on the rotary iteration transformation in the simplex method, an artificial variable return-to-zero (RZ) algorithm is proposed to decide whether some condition constraint in linear programming problem is geometrically superfluous or not, as turns the decision problem of condition constraint geometric superfluity into such one whether condition constraint set of equations in its normalized form has such feasible basis solution in which every component corresponding to artificial variable is nought. Moreover, with the help of this method above, a feasible way to simplify linear programming problem is obtained.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"6 1","pages":"56-59"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISKE.2010.5680794","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, based on the rotary iteration transformation in the simplex method, an artificial variable return-to-zero (RZ) algorithm is proposed to decide whether some condition constraint in linear programming problem is geometrically superfluous or not, as turns the decision problem of condition constraint geometric superfluity into such one whether condition constraint set of equations in its normalized form has such feasible basis solution in which every component corresponding to artificial variable is nought. Moreover, with the help of this method above, a feasible way to simplify linear programming problem is obtained.