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STUDY ON FUZZY OPTIMIZATION METHOD BASED ON QUASI-LINEAR FUZZY NUMBER

机译:基于拟线性模糊数的模糊优化方法研究

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By studying the structure of fuzzy information and the mechanism of fuzzy optimization, one concept, quasi-linear fuzzy number, is first proposed in this paper.It has been proven that quasi-linear fuzzy number can approach to any form of fuzzy number under Lp-metric.Second, by distinguishing principal indexes and assistant indexes, this paper gives the comparison method of fuzzy information based on synthesizing effect and the description method of fuzzy information on quasi-linear fuzzy number and principal indexes.Third, a new kind of fuzzy genetic algorithm based on quasi-linear fuzzy number is proposed (denoted by BQLFN-FGA).Finally, the results of the example indicate that our proposed algorithm not only possesses good performance and description, but also can effectively merge the decision consciousness with execution process of the algorithm, so it can be applied to any form of fuzzy optimization problems.
机译:通过研究模糊信息的结构和模糊优化的机理,本文首次提出了准线性模糊数的概念。事实证明,在Lp条件下,准线性模糊数可以逼近任何形式的模糊数。其次,通过区分主指标和辅助指标,给出了基于综合效果的模糊信息比较方法和准线性模糊数及其主指标的模糊信息描述方法。提出了一种基于准线性模糊数的遗传算法(用BQLFN-FGA表示)。最后,算例结果表明,该算法不仅具有良好的性能和描述性,而且可以有效地将决策意识与执行过程融合。该算法的适用范围,因此它可以应用于任何形式的模糊优化问题。

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