{"title":"多目标进化算法中一种新的权值设计","authors":"Fangqing Gu, Hai-Lin Liu","doi":"10.1109/CIS.2010.37","DOIUrl":null,"url":null,"abstract":"This paper presents a method to improve the performance of MOEA/D. The idea is to approximate the Pareto front(PF) by using a linear interpolation of the non-dominant solutions. It propose a novel weight design method for multi-objective evolutionary algorithm. Even when the PF is complex, we can obtain the Pareto optimal solutions which are distributed uniformly over the PF. Some test functions are constructed to compare the performance of the proposed algorithm with that of MOEA/D. The results indicate that the proposed algorithm could significantly outperform MOEA/D on these test instances.","PeriodicalId":420515,"journal":{"name":"2010 International Conference on Computational Intelligence and Security","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":"{\"title\":\"A Novel Weight Design in Multi-objective Evolutionary Algorithm\",\"authors\":\"Fangqing Gu, Hai-Lin Liu\",\"doi\":\"10.1109/CIS.2010.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method to improve the performance of MOEA/D. The idea is to approximate the Pareto front(PF) by using a linear interpolation of the non-dominant solutions. It propose a novel weight design method for multi-objective evolutionary algorithm. Even when the PF is complex, we can obtain the Pareto optimal solutions which are distributed uniformly over the PF. Some test functions are constructed to compare the performance of the proposed algorithm with that of MOEA/D. The results indicate that the proposed algorithm could significantly outperform MOEA/D on these test instances.\",\"PeriodicalId\":420515,\"journal\":{\"name\":\"2010 International Conference on Computational Intelligence and Security\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"41\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Computational Intelligence and Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.2010.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Computational Intelligence and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2010.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Weight Design in Multi-objective Evolutionary Algorithm
This paper presents a method to improve the performance of MOEA/D. The idea is to approximate the Pareto front(PF) by using a linear interpolation of the non-dominant solutions. It propose a novel weight design method for multi-objective evolutionary algorithm. Even when the PF is complex, we can obtain the Pareto optimal solutions which are distributed uniformly over the PF. Some test functions are constructed to compare the performance of the proposed algorithm with that of MOEA/D. The results indicate that the proposed algorithm could significantly outperform MOEA/D on these test instances.
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