非线性ae解集逼近的分支与剪枝算法

A. Goldsztejn
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引用次数: 28

摘要

非线性ae -解集是首先出现普遍量化参数的参数方程组的一种特殊情况。它们可以模拟许多实际情况。针对非线性ae解集的逼近问题,提出了一种新的分支和剪枝算法。它基于一种新的广义区间(区间的边界不受有序约束)参数Hansen-Sengupta算子。尽管ae解集的近似形式有一些限制,但它可以解决以前的数值方法无法解决的问题。提出了一些有前景的实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A branch and prune algorithm for the approximation of non-linear AE-solution sets
Non-linear AE-solution sets are a special case of parametric systems of equations where universally quantified parameters appear first. They allow to model many practical situations. A new branch and prune algorithm dedicated to the approximation of non-linear AE-solution sets is proposed. It is based on a new generalized interval (intervals whose bounds are not constrained to be ordered) parametric Hansen-Sengupta operator. In spite of some restrictions on the form of the AE-solution set which can be approximated, it allows to solve problems which were before out of reach of previous numerical methods. Some promising experimentations are presented.
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