构造最优化的直角斯坦纳树(rst)是一个NP完全问题。
It is proved that the problem of constructing an optimal Eectilinear Steiner Tree (RST) is NP-complete.
本文利用统计分析法，提出求解矩形斯坦纳树问题的多项式时间算法。
This paper presents a polynomial time algorithm for finding Rectilinear-Steiner-Trees by statistical analysis.
本文首先介绍了超大规模集成电路的物理设计流程，在此基础上引出直角斯坦纳树问题。
At first, this thesis introduces the VLSI physical design process, based on this leads to the rectilinear Steiner tree problem.
最后本文给出了在更高维空间的直角斯坦纳树问题的定义，和相应的最小凸多面体的构造。
Finally, this thesis gives the definition of the rectilinear Steiner tree problem in more higher-dimensional space, and the corresponding structure of the minimum convex polyhedron.
考虑了在带区间数据的不确定网络中，最小风险和模型以及最小最大风险模型下的斯坦纳树问题。
Based on the models of minimum risk sum and minimum maximum risk, this paper is concerned with the minimum Steiner tree problems in uncertain networks with interval data.
然后根据相关的优化理论，提出了求解时间目标数学模型的最小生成树算法和求解距离目标数学模型的最小矩形斯坦纳树算法。
According to the related optimizing theory, the Minimum Spanning Tree arithmetic and the Rectilinear SteinerMinimum Tree arithmetic were selected as the solution of the problem in this thesis.
然后根据相关的优化理论，提出了求解时间目标数学模型的最小生成树算法和求解距离目标数学模型的最小矩形斯坦纳树算法。
According to the related optimizing theory, the Minimum Spanning Tree arithmetic and the Rectilinear SteinerMinimum Tree arithmetic were selected as the solution of the problem in this thesis.
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