Title :
GA-based multi-objective optimization
Author :
Mingqiang, Li ; Jisong, Kou ; Lin, Dai
Author_Institution :
Inst. of Syst. Eng., Tianjin Univ., China
fDate :
6/22/1905 12:00:00 AM
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;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.860050
