Visualization of Pareto Optimal Solution Sets Using the Growing Hierarchical Self-Organizing Maps

被引：2
|
作者：
Suzuki, Naoto [1 ]
Okamoto, Takashi [2 ]
Koakutsu, Seiichi [2 ]
机构：
[1] Chiba Univ, Grad Sch Engn, Masters Program, Div Artificial Syst Sci, Chiba, Japan
[2] Chiba Univ, Grad Sch Engn, Chiba, Japan
来源：
ELECTRONICS AND COMMUNICATIONS IN JAPAN | 2017年 / 100卷 / 01期
基金：
日本学术振兴会;
关键词：
multiobjective optimization; Pareto optimal solution set; visualization; self-organizing maps; GHSOM; DESIGN;
D O I：
10.1002/ecj.11915
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The visualization of the Pareto optimal solution set is one of important issues of the multiobjective optimization. The Pareto optimal solution visualization method using the self-organizing maps is one of promising visualization methods. This method has two shortcomings. One is that the map size has to be determined in advance. The other is that infeasible solutions can appear in the learnt maps. This paper proposes a new visualization technique using the growing hierarchical SOM (GHSOM), which is expected to solve foregoing shortcomings. This paper also proposes to introduce a symmetric transformation of maps into the learning algorithm in order to obtain easily viewable unified map. The effectiveness of the proposed method is confirmed through several numerical experiments.
引用
收藏
页码：3 / 17
页数：15
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