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Abstract
Although a number of multiobjective evolutionary algorithms have been proposed over the last two decades, not much effort has been made to deal with variable linkages in multiobjective optimization. Recently, we have suggested a general framework of multiobjective evolutionary algorithms based on decomposition (MOEA/D) [1]. MOEA/D decomposes a MOP into a number of scalar optimization subproblems by a conventional decomposition method. The optimal solution to each of these problems is a Pareto optimal solution to the MOP under consideration. An appropriate decomposition could make these individual Pareto solutions evenly distribute along the Pareto optimal front. MOEA/D aims at solving these scalar optimization subproblems simultaneously. In this paper, we propose, under the framework of MOEA/D, a multiobjective differential evolution based decomposition (MODE/D) for tackling variable linkages. Our experimental results show that MODE/D outperforms several other MOEAs on several test problems with variable linkages.
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Department of Computer Science, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, United Kingdom
Hui Li & Qingfu Zhang
- Hui Li
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- Qingfu Zhang
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Editors and Affiliations
Science Institute, University of Iceland, P.O. Box, Iceland
Thomas Philip Runarsson
Vorarlberg University of Applied Sciences, Hochschulstr. 1, A-6850, Dornbirn, Austria
Hans-Georg Beyer
Automated Scheduling, Optimisation and Planning Group, School of Computer Science & IT, University of Nottingham, NG8 1BB, Nottingham, UK
Edmund Burke
Depto. Arquitectura y Tecnologa de Computadores, ETS Ingeiera Informtica, C/Daniel Saucedo Aranda, s/n, 18071, Granada, Spain
Juan J. Merelo-Guervós
Colorado State University, 80523, Fort Collins, CO, USA
L. Darrell Whitley
University of Birmingham, Birmingham, UK
Xin Yao
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Li, H., Zhang, Q. (2006). A Multiobjective Differential Evolution Based on Decomposition for Multiobjective Optimization with Variable Linkages. In: Runarsson, T.P., Beyer, HG., Burke, E., Merelo-Guervós, J.J., Whitley, L.D., Yao, X. (eds) Parallel Problem Solving from Nature - PPSN IX. PPSN 2006. Lecture Notes in Computer Science, vol 4193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11844297_59
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