Solving many-objective optimization problems using set-based evolutionary algorithms

被引：0
作者：
机构：
[1] School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou
来源：
Gong, D.-W. (dwgong@vip.163.com) | 1600年 / Chinese Institute of Electronics卷 / 42期
关键词：
Evolutionary algorithm; Many-objective optimization; Set-based evolution; User preference;
D O I：
10.3969/j.issn.0372-2112.2014.01.012
中图分类号：
学科分类号：
摘要：
Previous methods are difficult to tackle a many-objective optimization problem since it contains many objectives. A set-based evolutionary algorithm was proposed to effectively solve the above problem in this study. In the proposed method, the original optimization problem was first transformed into a tri-objective one by taking such indicators as hyper-volume, distribution and spread as three new objectives; thereafter, a set-based Pareto dominance relation was defined, and a fitness function reflecting a user's preference was designed; additionally, set-based evolutionary strategies were suggested. The proposed method was applied to four benchmark many-objective optimization problems and compared with the other two methods. The experimental results show its advantages.
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页码：77 / 83
页数：6
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