{"title":"遗传算法的多目标分式规划","authors":"D. Roy, R. Dasgupta","doi":"10.1109/ICRCICN.2016.7813644","DOIUrl":null,"url":null,"abstract":"Efficiency of any system or organization can be dealt as output divided by input. In case an organization has multiple inputs, the effective input can be treated as a linear combination of inputs and similarly output can be treated as a combination of outputs. This ratio of the linear combination of output divided by input is a fraction. Optimization of this multivariable fraction is a mathematical challenge. A system may have multiple such ratios to be optimized, where independent variables are same in all the fractional functions. Though there is a large number of numerical algorithms for solving such an abnormal function, it has been found genetic algorithm performs far better. In this paper a new way of obtaining the Pareto Optimal front for the Multi Objective Optimisation problem consisting of multiple fractions has been demonstrated using Genetic Algorithm implemented in MATLAB.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multi objective fractional programming by genetic algorithm\",\"authors\":\"D. Roy, R. Dasgupta\",\"doi\":\"10.1109/ICRCICN.2016.7813644\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Efficiency of any system or organization can be dealt as output divided by input. In case an organization has multiple inputs, the effective input can be treated as a linear combination of inputs and similarly output can be treated as a combination of outputs. This ratio of the linear combination of output divided by input is a fraction. Optimization of this multivariable fraction is a mathematical challenge. A system may have multiple such ratios to be optimized, where independent variables are same in all the fractional functions. Though there is a large number of numerical algorithms for solving such an abnormal function, it has been found genetic algorithm performs far better. In this paper a new way of obtaining the Pareto Optimal front for the Multi Objective Optimisation problem consisting of multiple fractions has been demonstrated using Genetic Algorithm implemented in MATLAB.\",\"PeriodicalId\":254393,\"journal\":{\"name\":\"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRCICN.2016.7813644\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRCICN.2016.7813644","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi objective fractional programming by genetic algorithm
Efficiency of any system or organization can be dealt as output divided by input. In case an organization has multiple inputs, the effective input can be treated as a linear combination of inputs and similarly output can be treated as a combination of outputs. This ratio of the linear combination of output divided by input is a fraction. Optimization of this multivariable fraction is a mathematical challenge. A system may have multiple such ratios to be optimized, where independent variables are same in all the fractional functions. Though there is a large number of numerical algorithms for solving such an abnormal function, it has been found genetic algorithm performs far better. In this paper a new way of obtaining the Pareto Optimal front for the Multi Objective Optimisation problem consisting of multiple fractions has been demonstrated using Genetic Algorithm implemented in MATLAB.