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FINDING ALL MINIMIZING POINTS OF BI-QUADRATIC SURFACE BY SET-ORIENTED BRANCHING

机译:通过定向的分支找到所有最小化双二次表面的点

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There are many useful iterative methods for optimization, but there are global optimization problems that can not be solved by iterative methods and non-iterative methods are required for such problems. In this article, a novel and non-iterative approach is presented for finding all the minimizing points of two-dimensional bi-quadratic spline surface under a box constraint. It is shown that the feasible set can be divided into finitely many branches according to the properties of the objective function and that the problem of finding all the minimizing points can be reduced to a finite combination of one dimensional solvable optimization problems. The idea of choosing the branches according to the structure of the objective function is detailed and a transformation of the objective function is proposed for the reduction of the problem dimension.
机译:优化有许多有用的迭代方法,但是存在全局优化问题,无法通过迭代方法解决,并且需要非迭代方法进行此类问题。在本文中,提出了一种新颖和非迭代方法,用于在盒子约束下找到二维双二次样条状表面的所有最小化点。结果表明,可行的设定可以根据目标函数的特性分为许多分支,并且可以减少找到所有最小化点的问题,以减少到一个维度可溶性优化问题的有限组合。根据物镜函数的结构选择分支的想法是详细的,并且提出了用于减少问题尺寸的目标函数的变换。

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