Visualization Technique for Analyzing Non-dominated Set Comparison

  title={Visualization Technique for Analyzing Non-dominated Set Comparison},
  author={Kiam Heong Ang and Gregory Chong and Yun Li},
Multi-objective evolutionary algorithms (MOEAs) have been proved successfully in many different applications. Over 900 publications [4] have since proposed various MOEA implementations and applications. However, there is still a significant lack of studies on metrics for MOEA comparison. In this paper, we propose a new visualization technique that will provide better analysis of the nondominated solutions for any number of objectives. 

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 11 extracted citations

Design metrics and visualization techniques for analyzing the performance of MOEAs in DSE

2011 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation • 2011
View 1 Excerpt


Publications referenced by this paper.
Showing 1-10 of 17 references


R. Sarker
Mohammadian and X. Yao (eds), “Evolutionary Optimization”, Kluwer Academic Publishers, New York • 2002
View 1 Excerpt

Preliminary Statement on the Current Progress of Multi-Objective Evolutionary Algorithm Performance Measurement

K. H. Ang, G. Chong, Y. Li
Proceedings of the 2002 Congress on Evolutionary Computation • 2002
View 1 Excerpt

An Overview of Benchmarking Techniques for Multi-Objective Evolutionary Algorithms

K. H. Ang, Y. Li
Proceedings of the 6 Online World Conference on Soft Computing in Industrial Applications (WSC6), pp. 337-348, Internet • 2001
View 1 Excerpt

A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II

K. Deb, A. Pratap, S. Agarwal, T. Meyarivan
KanGAL report 200001, Indian Institute of Technology, Kanpur, India • 2000
View 1 Excerpt

A Comprehensive Survey of Evolutionary-Based Multiobjective Optimization Techniques

C.A.C. Coello
Knowledge and Information Systems, An International Journal, • 1999

Similar Papers

Loading similar papers…