Finding solvable subsets of constraint graphs

被引:0
|
作者
Hoffmann, CM [1 ]
Lomonosov, A
Sitharam, M
机构
[1] Purdue Univ, W Lafayette, IN 47907 USA
[2] Kent State Univ, Kent, OH 44242 USA
关键词
extremal subgraph; dense graph; network flow; combinatorial optimization; constraint solving; geometric constraint graph; geometric modeling;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a network flow based, degree of freedom analysis for graphs that arise in geometric constraint systems. For a vertex and edge weighted constraint graph with m edges and n vertices, we give an O(n(m + n)) time max-flow based algorithm to isolate a subgraph that can be solved separately. Such a subgraph is called dense. If the constraint problem is not overconstrained, the subgraph will be minimal. For certain overconstrained problems, finding minimal dense subgraphs may require up to O(n(2)(m + n)) steps. Finding a minimum dense subgraph is NP-hard. The algorithm has been implemented and consistently outperforms a simple but fast, greedy algorithm.
引用
收藏
页码:463 / 477
页数:15
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