Multi-objective optimisation in the presence of uncertainty

Author

Fieldsend, Jonathan E. ; Everson, Richard M.

Author_Institution

Dept. of Comput. Sci., Exeter Univ.

Volume

1

fYear

2005

fDate

5-5 Sept. 2005

Firstpage

243

Lastpage

250

Abstract

There has been only limited discussion on the effect of uncertainty and noise in multi-objective optimization problems and how to deal with it. We address this problem by assessing the probability of dominance and maintaining an archive of solutions which are, with some known probability, mutually non-dominating. We examine methods for estimating the probability of dominance. These depend crucially on estimating the effective noise variance and we introduce a novel method of learning the variance during optimization. Probabilistic domination contours are presented as a method for conveying the confidence that may be placed in objectives that are optimized in the presence of uncertainty

Keywords

estimation theory; evolutionary computation; noise; optimisation; probability; estimation theory; multiobjective optimization; noise variance; probabilistic domination contour; Computer aided manufacturing; Computer science; Design optimization; Error analysis; Evolutionary computation; Measurement errors; Optimization methods; Pattern recognition; Stochastic systems; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2005. The 2005 IEEE Congress on

Conference_Location

Edinburgh, Scotland

Print_ISBN

0-7803-9363-5

Type

conf

DOI

10.1109/CEC.2005.1554691

Filename

1554691