{"title":"Reference Points Generated on Unit Hypersurfaces for MaOEAs","authors":"Haruto Takeuchi, Md. Kawsar Khan, M. Ohki","doi":"10.1109/3ICT53449.2021.9581958","DOIUrl":null,"url":null,"abstract":"This paper proposes a method to uniformly generate reference points on a hypersurface for many-objective optimization evolutionary algorithms (MaOEAs). Recently, MaOEAs have been proposed to obtain selection pressure in a multidimensional objective space by using a reference point set, but there is no method for generating a reference point set that is supposed to incorporate user orientation. This paper proposes a method for generating uniform reference points on unit hyperspheres and unit hyperplanes in a multidimensional objective space. The proposed method is applied to the multi-objective genetic programming (GP) problem by non-dominated sorting genetic algorithm-III (NSGA-III) and to the multi-objective combinatorial optimization problem by multiobjective evolutionary algorithm based on decomposition (MOEA/D). As a result, we confirm that the proposed method gives non-inferior results compared to conventional methods. Since the proposed method can easily incorporate user orientation, this shows the effectiveness of the proposed method.","PeriodicalId":133021,"journal":{"name":"2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/3ICT53449.2021.9581958","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
This paper proposes a method to uniformly generate reference points on a hypersurface for many-objective optimization evolutionary algorithms (MaOEAs). Recently, MaOEAs have been proposed to obtain selection pressure in a multidimensional objective space by using a reference point set, but there is no method for generating a reference point set that is supposed to incorporate user orientation. This paper proposes a method for generating uniform reference points on unit hyperspheres and unit hyperplanes in a multidimensional objective space. The proposed method is applied to the multi-objective genetic programming (GP) problem by non-dominated sorting genetic algorithm-III (NSGA-III) and to the multi-objective combinatorial optimization problem by multiobjective evolutionary algorithm based on decomposition (MOEA/D). As a result, we confirm that the proposed method gives non-inferior results compared to conventional methods. Since the proposed method can easily incorporate user orientation, this shows the effectiveness of the proposed method.