Title :
Multiobjective optimization using a Pareto differential evolution approach
Author :
Madavan, Nateri K.
Author_Institution :
NASA Adv. Supercomput. Div., NASA Ames Res. Center, Moffett Field, CA, USA
fDate :
6/24/1905 12:00:00 AM
Abstract :
Differential evolution is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. In this paper, the differential evolution algorithm is extended to multiobjective optimization problems by using a Pareto-based approach. The algorithm performs well when applied to several test optimization problems from the literature
Keywords :
evolutionary computation; optimisation; Pareto differential evolution approach; evolutionary algorithm; global optimum; multiobjective optimization; Electronic switching systems; Evolutionary computation; Genetic algorithms; NASA; Optimization methods; Pareto optimization; Performance evaluation; Robustness; Sorting; Testing;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1004404
