本研究探討多目標最佳化方法，其中結合模糊理論及演進式規劃法則，引入非劣效性概念特徵化多目標最佳化方法之解決方案，利用基於演進式規劃中的模糊滿足條件，規劃最佳化解答。因此，最佳化之目標函數將以模糊集表示，描述目標函數的不確定性。本研究建立一分時性程式以多目標操作條件達成饋線重組之最佳化，藉以解決一電力配置系統之方案。本案結果提出一有效解決多目標最佳化之演算法，並有效率的允許使用於模糊真實大型系統的最佳化方案。
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 introduced to determine the optimal solution. As a result, the objective functions of the optimization problem are modeled with fuzzy sets to represent their imprecise nature. 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.
