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- Publisher
- Springer Journals
- Copyright
- Copyright © 2005 by Springer
- Subject
- Computer Science; Artificial Intelligence (incl. Robotics); Computer Science, general
- ISSN
- 0269-2821
- eISSN
- 1573-7462
- DOI
- 10.1007/s10462-004-2902-3
- Publisher site
- See Article on Publisher Site
Abstract
This paper reviews a number of popular distribution preservation mechanisms and examines their characteristics and effectiveness in evolutionary multi-objective (MO) optimization. A conceptual framework consisting of solution assessment and elitism is presented to better understand the search guidance in evolutionary MO optimization. Simulation studies among different distribution preservation techniques are performed over fifteen representative distribution samples and the performances are compared based upon two distribution metrics proposed in this paper. The results and findings reported in this paper are valuable for better understanding of the working principle and characteristics of distribution preservation mechanisms, which are very useful for incorporating different distribution preservation features into MO evolutionary algorithms in a modular fashion or improving the effectiveness of existing preservation approaches.
Journal
Artificial Intelligence Review – Springer Journals
Published: Sep 23, 2004