迭代压缩:图和电路平分的改进方法

J. Haralambides, F. Makedon
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引用次数: 3

摘要

给定一个图G=(V,E),图平分是在两个大小相等的子集V/sub 1/和V/sub 2/中找到顶点集V的分区,使它们之间的边数最小的问题。该问题在电路划分、测试、VLSI设计和其他应用分治策略的网络相关问题中具有重要的应用。本文提出了一种新的启发式算法,即迭代压缩算法(IC),它采用了基于节点度的匹配和迭代图压缩算法。这在时间和结果质量上都比已知的对分算法有了显著的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Iterative compaction: an improved approach to graph and circuit bisection
Given a graph G=(V,E), graph bisection is the problem of finding a partition of the vertex set V in two equal-sized subsets V/sub 1/ and V/sub 2/ so that the number of edges between them is minimized. This problem has important applications in circuit partitioning, testing, VLSI design and other network-related problems that apply the divide-and-conquer strategy. The authors introduce a new heuristic approach, called iterative compaction (IC), which employees a node degree based matching and iterative graph compaction. This gives a significant improvement over the performance of known bisection algorithms in both time and quality of the results.<>
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