{"title":"Multi-objective optimization problems: Method and application","authors":"Fatimah Sham, Ismail, K. Lumpur., Malaysia","doi":"10.1109/ICMSAO.2011.5775623","DOIUrl":null,"url":null,"abstract":"Self organizing genetic algorithm (SOGA) is a class of heuristic multi-objective optimization method that has high capabilities for solving multiple conflicting objective functions. This paper presents an application of SOGA for optimizing multi-objectives components placement of multi voltage regulator (MVR) system on printed circuit board by considering multi-constraint parameters. The simulation results, which are developed based on experimental measurement, show that the SOGA can propose better optimal solution compared to the initial design.","PeriodicalId":6383,"journal":{"name":"2011 Fourth International Conference on Modeling, Simulation and Applied Optimization","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Fourth International Conference on Modeling, Simulation and Applied Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMSAO.2011.5775623","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Self organizing genetic algorithm (SOGA) is a class of heuristic multi-objective optimization method that has high capabilities for solving multiple conflicting objective functions. This paper presents an application of SOGA for optimizing multi-objectives components placement of multi voltage regulator (MVR) system on printed circuit board by considering multi-constraint parameters. The simulation results, which are developed based on experimental measurement, show that the SOGA can propose better optimal solution compared to the initial design.
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