GA-based multi-objective optimization

Author

Mingqiang, Li ; Jisong, Kou ; Lin, Dai

Author_Institution

Inst. of Syst. Eng., Tianjin Univ., China

Volume

1

fYear

2000

fDate

6/22/1905 12:00:00 AM

Firstpage

637

Abstract

Proposes a hybrid algorithm for finding a set of multi-solutions of multi-objective optimization problems. In the proposed algorithm, a genetic algorithm is adopted to solve the multi-modal function optimization problem, a local search procedure is applied to each solution generated by genetic operations. The aim of the proposed algorithm is not only to determine the global optimal solution, but also to try to find all the non-dominated solutions of a multi-objective optimization problem. The choice of the final solution set is left to the decision maker´s preference. High search ability of the proposed algorithm is demonstrated by computer simulation

Keywords

decision theory; genetic algorithms; search problems; decision maker´s preference; genetic operations; global optimal solution; high search ability; hybrid algorithm; local search procedure; multi-modal function optimization; multi-objective optimization; solution set; Algorithm design and analysis; Application software; Computer simulation; Design optimization; Diversity reception; Genetic algorithms; Genetic mutations; Iterative methods; Pareto optimization; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on

Print_ISBN

0-7803-5995-X

Type

conf

DOI

10.1109/WCICA.2000.860050

Filename

860050