Abstract
The purpose of this paper is to address the multi-objective optimization via combined fuzzy satisfied method and evolution programming (E.P.) method. The concept of non-inferiority is employed to characterize a solution of the multi-objective problem. Then, a fuzzy satisfied method based on evolutionary programming is introduce d to determine the optimal solution. As a result, the objective functions of the optimization problem are modeled with fuzzy sets to represent their imprecise natur e. That also enables us to reduce the inaccuracies in decision-makers' judgments. A time-sharing computer program is implemented, and an application to a multi-objective operation problem in feeder reconfiguration in electric power systems is demonstrated along with the computer outputs. In conclusion, the proposed solution algorithm allows for a more realistic problem formulation efficiently obtained the optimal solution for the tested system with a large search space.
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