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Tchebycheff approximation in Gaussian Process model composition for multi-objective expensive black box

Liu, W and Zhang, Q and Tsang, E and Virginas, B (2008) Tchebycheff approximation in Gaussian Process model composition for multi-objective expensive black box. In: UNSPECIFIED, ? - ?.

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Abstract

Black-box expensive function is ubiquitous in real world problems. Much research has been done on scalar objective optimization for such problems with great success. Comparatively, very little work has been done in multi-objective optimization. In many cases, it is not straightforward to convert methods from scalar objective optimization to multi-objective optimization due to the complexities incurred by Pareto domination. In our pervious research, concept of model composition based on Gaussian Process metamodel and the powerful MOEA/D framework proved to be a successful approach for multiobjective optimization with black-box expensive functions. We derived Weighted-Sum and Tchebycheff model composition for bi-objective problems. However, due to the complexity of Tchebycheff decomposition structure, it is very hard, if not impossible, to extend the method to three or more objective problems in a nature way. In this paper, we propose an approximation method for Tchebycheff model composition which greatly simplify the derivation for three or more objective cases. Experiments show the approximation produces very similar performance as the Weighted-Sum and Tchebycheff without approximation. Thus, the new method enables us to tackle multi-objective problems with black-box expensive functions that could not be tackled effectively so far. © 2008 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2008 IEEE Congress on Evolutionary Computation, CEC 2008
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 15 Aug 2012 13:46
Last Modified: 30 Jan 2019 16:16
URI: http://repository.essex.ac.uk/id/eprint/1978

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