Affiliation of Author(s):计算机科学与技术学院/人工智能学院/软件学院
Journal:Proc. - Int. Conf. Ind. Inf. - Comput. Technol., Intell. Technol., Ind. Inf. Integr., ICIICII
Abstract:How to balance the diversity and convergence plays an important role on the performance of a multiobjective evolutionary optimizer. Due to the loss of selection pressure and the exponential expansion in the high-dimensional objective space, it is even more difficult for an optimizer to balance between convergence and diversity for a many-objective optimization problem. To address this issue, in this paper, we propose a cache mechanism to improve the convergence and a coverage-based method for maintaining better diversity. Based on these two mechanisms, a many-objective evolutionary algorithm is further proposed. The experimental studies are conducted to verify the effectiveness of the proposed approach. © 2017 IEEE.
Translation or Not:no
Date of Publication:2018-03-29
Co-author:Sun, Haoran,Sulaman, Muhammad,Fan, Zhun
Correspondence Author:czz
Date of Publication:2018-03-29