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在模糊环境下的优化向来是模糊系统理论的中心课题之一。文献中所见的绝大多数模糊系统优化技术都以线性规划为基础。本文提出了一种完全不同的模糊系统试化方法——启发式试化方法。这种方法以系统的模糊模型为基础,它允许以模糊形式表达的性能指标与约束。试化的结果,亦即最优决策,既可以是模糊值,也可以是精确值。由于所使用的模糊模型所以看作是一个规则集,所提出的试化方法便所以视作一个“剪枝”过程。一个数值例子说明了这种试化方法的有效性。
Optimization in the fuzzy environment has always been one of the central topics of fuzzy system theory. Most of the fuzzy system optimization techniques seen in the literature are based on linear programming. In this paper, we present a completely different fuze system test method - heuristic test method. This method is based on a systematic fuzzy model that allows for performance metrics and constraints expressed in a fuzzy form. The result of the trial, which is the optimal decision, can be both fuzzy and exact. Since the fuzzy model used is therefore considered as a set of rules, the proposed method of testing is considered a “pruning” process. A numerical example illustrates the effectiveness of this test method.