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Global optimization for a class of fractional programming problems

机译:一类分数规划问题的全局优化

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This paper presents a canonical dual approach to minimizing the sum of a quadratic function and the ratio of two quadratic functions, which is a type of non-convex optimization problem subject to an elliptic constraint. We first relax the fractional structure by introducing a family of parametric subproblems. Under proper conditions on the "problem-defining" matrices associated with the three quadratic functions, we show that the canonical dual of each subproblem becomes a one-dimensional concave maximization problem that exhibits no duality gap. Since the infimum of the optima of the parameterized subproblems leads to a solution to the original problem, we then derive some optimality conditions and existence conditions for finding a global minimizer of the original problem. Some numerical results using the quasi-Newton and line search methods are presented to illustrate our approach.
机译:本文提出了一种规范对偶方法,以最小化二次函数之和和两个二次函数之比,这是一类受椭圆约束的非凸优化问题。我们首先通过引入一系列参数子问题来放松分数结构。在与三个二次函数相关联的“问题定义”矩阵的适当条件下,我们表明,每个子问题的规范对偶变成一维凹面最大化问题,没有任何对偶间隙。由于参数化子问题的最优解的不足导致了原始问题的解决方案,因此我们导出了一些最优性条件和存在条件,以找到原始问题的全局最小化子。提出了一些使用拟牛顿法和线搜索法的数值结果,以说明我们的方法。

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