{"title":"基于主成分分析和网格划分的多目标进化算法","authors":"Mei Ma, Hecheng Li, Jing Huang","doi":"10.1109/CIS2018.2018.00051","DOIUrl":null,"url":null,"abstract":"In order to effectively solve the many objective optimization problems (MaOPs), a new multi-objective evolutionary algorithm is proposed. Firstly, utilizes the principal component analysis (PCA) to reduce the dimension of objective space. The main idea is do a correlation analysis between objectives. Secondly, puts forward a new grid division method. In the course of dividing, make sure all grid sizes are equal. The simulation illustrates the efficiency of the proposed algorithm.","PeriodicalId":185099,"journal":{"name":"2018 14th International Conference on Computational Intelligence and Security (CIS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Multi-Objective Evolutionary Algorithm Based on Principal Component Analysis and Grid Division\",\"authors\":\"Mei Ma, Hecheng Li, Jing Huang\",\"doi\":\"10.1109/CIS2018.2018.00051\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to effectively solve the many objective optimization problems (MaOPs), a new multi-objective evolutionary algorithm is proposed. Firstly, utilizes the principal component analysis (PCA) to reduce the dimension of objective space. The main idea is do a correlation analysis between objectives. Secondly, puts forward a new grid division method. In the course of dividing, make sure all grid sizes are equal. The simulation illustrates the efficiency of the proposed algorithm.\",\"PeriodicalId\":185099,\"journal\":{\"name\":\"2018 14th International Conference on Computational Intelligence and Security (CIS)\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 14th International Conference on Computational Intelligence and Security (CIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS2018.2018.00051\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 14th International Conference on Computational Intelligence and Security (CIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS2018.2018.00051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Multi-Objective Evolutionary Algorithm Based on Principal Component Analysis and Grid Division
In order to effectively solve the many objective optimization problems (MaOPs), a new multi-objective evolutionary algorithm is proposed. Firstly, utilizes the principal component analysis (PCA) to reduce the dimension of objective space. The main idea is do a correlation analysis between objectives. Secondly, puts forward a new grid division method. In the course of dividing, make sure all grid sizes are equal. The simulation illustrates the efficiency of the proposed algorithm.
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