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Global Optimization of a Quadratic Functional with Quadratic Equality Constraints, Part 2

机译:具有二次等式约束的二次函数的全局优化,第2部分

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摘要

In this paper, we investigate a constrained optimization problem with a quadratic cost functional and two quadratic equality constraints. It is assumed that the cost functional is positive definite and that the constraints are both feasible and regular (but otherwise they are unrestricted quadratic functions). Thus, the existence of a global constrained minimum is assured. We develop a necessary and sufficient condition that completely characterizes the global minimum cost. Such a condition is of essential importance in iterative numerical methods for solving the constrained minimization problem, because it readily distinguishes between local minima and global minima and thus provides a stopping criterion for the computation. The result is similar to one obtained previously by the authors. In the previous result, we gave a characterization of the global minimum of a constrained quadratic minimization problem in which the cost functional was an arbitrary quadratic functional (as opposed to positive-definite here) and the constraints were at least positive-semidefinite quadratic functions (as opposed to essentially unrestricted here).
机译:在本文中,我们研究了具有二次成本函数和两个二次等式约束的约束优化问题。假定成本函数是正定的,并且约束既可行又规则(但否则它们是不受限制的二次函数)。因此,确保了全局约束最小值的存在。我们开发了一个充分描述全球最低成本的必要条件。这样的条件在解决约束最小化问题的迭代数值方法中至关重要,因为它可以轻松地区分局部最小值和全局最小值,从而为计算提供了停止标准。结果类似于作者先前获得的结果。在之前的结果中,我们描述了约束二次最小化问题的全局最小值,其中成本函数是任意二次函数(此处与正定相反),而约束条件至少是正半定二次函数(与此处基本不受限制的相反)。

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