Towards a quick computation of well-spread pareto-optimal solutions

Deb, Kalyanmoy ; Mohan, Manikanth ; Mishra, Shikhar (2003) Towards a quick computation of well-spread pareto-optimal solutions Lecture Notes in Computer Science, 2632/2003 . p. 68. ISSN 0302-9743

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The trade-off between obtaining a good distribution of Pareto-optimal solutions and obtaining them in a small computational time is an important issue in evolutionary multi-objective optimization (EMO). It has been well established in the EMO literature that although SPEA produces a better distribution compared to NSGA-II, the computational time needed to run SPEA is much larger. In this paper, we suggest a clustered NSGA-II which uses an identical clustering technique to that used in SPEA for obtaining a better distribution. Moreover, we propose a steady-state MOEA based on ε-dominance concept and effcient parent and archive update strategies. Based on a comparative study on a number of two and three objective test problems, it is observed that the steady-state MOEA achieves a comparable distribution to the clustered NSGA-II with a much less computational time.

Item Type:Article
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ID Code:83514
Deposited On:21 Feb 2012 07:10
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