An improved performance metric for multiobjective evolutionary algorithms with user preferences

Yu, G, Zheng, J and Li, X 2015, 'An improved performance metric for multiobjective evolutionary algorithms with user preferences', in Proceedings of Congress of Evolutionary Computation (CEC), Sendai, Japan, 25-28 May 2015, pp. 908-915.


Document type: Conference Paper
Collection: Conference Papers

Title An improved performance metric for multiobjective evolutionary algorithms with user preferences
Author(s) Yu, G
Zheng, J
Li, X
Year 2015
Conference name IEEE 2015 Congress of Evolutionary Computation (CEC),
Conference location Sendai, Japan
Conference dates 25-28 May 2015
Proceedings title Proceedings of Congress of Evolutionary Computation (CEC)
Publisher IEEE
Place of publication Red Hook, United States
Start page 908
End page 915
Total pages 8
Abstract This paper proposes an improved performance metric for multiobjective evolutionary algorithms with user preferences. This metric uses the idea of decomposition to transform the preference information into m+1 points on a constructed preference-based hyperplane, then calculates the Euclidean distances and the angles between the obtained solutions by algorithms and those obtained m+1 points, respectively. By means of these distances and angles, the proposed metric can evaluate effectively both the convergence and diversity of the obtained solution set, with consideration of the preference information. This makes easier and allows meaningful comparisons between different multiobjective evolutionary algorithms using preference information.
Subjects Neural, Evolutionary and Fuzzy Computation
Copyright notice © 2015 IEEE
ISBN 9781479974924
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