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首页> 外文期刊>Soft computing: A fusion of foundations, methodologies and applications >An approach for solving a fuzzy bilevel programming problem through nearest interval approximation approach and KKT optimality conditions
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An approach for solving a fuzzy bilevel programming problem through nearest interval approximation approach and KKT optimality conditions

机译:一种通过最近的间隔近似方法和KKT最优性条件解决模糊贝尔编程问题的方法

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摘要

In this paper, we consider a kind of bilevel linear programming problem where the coefficients of both objective functions are fuzzy numbers. In order to deal with such a problem, the original problem can be approximated by an interval bilevel programming problem in terms of the nearest interval approximation of a fuzzy number. Based on the Karush-Kuhn-Tucker (KKT) optimality conditions for the optimization problem with an interval-valued objective function, the interval bilevel programming problem can be converted into a single-level programming problem with an interval-value objective function. To minimize the interval objective function, the order relations of interval numbers are used to transform the uncertain single-objective optimization into a multi-objective optimization solved by global criteria method (GCM). Finally, illustrative numerical examples are provided to demonstrate the feasibility of the proposed approach.
机译:在本文中,我们考虑了一种彼此线性编程问题,其中两个目标函数的系数是模糊数。 为了处理这样的问题,可以根据模糊数的最接近的间隔近似,原始问题近似于间隔的彼此编程问题。 基于Karush-Kuhn-tucker(KKT)的优化问题,通过间隔值的目标函数进行优化问题,间隔彼此编程问题可以通过间隔值目标函数转换为单级编程问题。 为了最小化间隔目标函数,间隔数的顺序关系用于将不确定的单目标优化转换为全球标准方法(GCM)解决的多目标优化。 最后,提供了说明性的数值例子以证明所提出的方法的可行性。

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