A new multiobjective evolutionary algorithm: OMOEA

Author

Zeng, San You ; Ding, Lixin ; Chen, Yuping ; Kang, Lishan

Author_Institution

Dept. Comput. Sci., China Univ. of GeoSci., Hubei, China

Volume

2

fYear

2003

fDate

8-12 Dec. 2003

Firstpage

898

Abstract

A new algorithm is proposed to solve constrained multiobjective problems. The constraints of the MOPs are taken account of in determining Pareto dominance. As a result, the feasibility of solutions is not an issue. At the same time, it takes advantage of both the orthogonal design method to search evenly, and the statistical optimal method to speed up the computation. The output of the technique is a large set of solutions with high precision and even distribution. Notably, for an engineering problem WATER, it finds the Pareto-optimal set, which was previously unknown.

Keywords

Pareto optimisation; constraint theory; design; evolutionary computation; MOP; OMOEA; Pareto-optimal set; WATER engineering problem; constrained multiobjective problem; evolutionary algorithm; optimization; orthogonal general design method; statistical optimal method; Algorithm design and analysis; Computer science; Design methodology; Design optimization; Evolutionary computation; Genetic algorithms; Geology; Laboratories; Software engineering; Sorting;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2003. CEC '03. The 2003 Congress on

Print_ISBN

0-7803-7804-0

Type

conf

DOI

10.1109/CEC.2003.1299762

Filename

1299762