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A Classification Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization

Pan, Linqiang, He, Cheng, Tian, Ye, Wang, Handing, Zhang, Xingyi and Jin, Yaochu (2018) A Classification Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization IEEE Transactions on Evolutionary Computation.

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Abstract

Surrogate-assisted evolutionary algorithms have been developed mainly for solving expensive optimization problems where only a small number of real fitness evaluations are allowed. Most existing surrogate-assisted evolutionary algorithms are designed for solving low-dimensional single or multiobjective optimization problems, which are not well suited for many-objective optimization. This paper proposes a surrogateassisted many-objective evolutionary algorithm that uses an artificial neural network to predict the dominance relationship between candidate solutions and reference solutions instead of approximating the objective values separately. The uncertainty information in prediction is taken into account together with the dominance relationship to select promising solutions to be evaluated using the real objective functions. Our simulation results demonstrate that the proposed algorithm outperforms the state-of-the-art evolutionary algorithms on a set of manyobjective optimization test problems.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Computing Science
Authors :
NameEmailORCID
Pan, Linqiang
He, Cheng
Tian, Ye
Wang, Handinghanding.wang@surrey.ac.uk
Zhang, Xingyi
Jin, YaochuYaochu.Jin@surrey.ac.uk
Date : 5 February 2018
Funders : Engineering and Physical Sciences Research Council (EPSRC)
Identification Number : 10.1109/TEVC.2018.2802784
Copyright Disclaimer : © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Uncontrolled Keywords : Surrogate-assisted evolutionary optimization; Pareto dominance; Expensive many-objective optimization; Classification
Depositing User : Clive Harris
Date Deposited : 09 Feb 2018 11:13
Last Modified : 22 Mar 2018 10:10
URI: http://epubs.surrey.ac.uk/id/eprint/845791

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