加权超图在循环内嵌入的算法与复杂度

S. L. Lee, Hann-Jang Ho
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引用次数: 14

摘要

加权超图嵌入循环(WHEC)问题是将一个超图的加权超边嵌入到一个循环中的路径中,从而使循环中任何物理链路的最大拥塞最小化。这个问题的一个更简单的版本是加权图嵌入循环(WGEC),它将法向图的加权边嵌入到循环中的路径中。WHEC和WGEC问题在设计自动化、并行计算和计算机通信等领域具有广泛的应用。本文首先证明了WHEC和WGEC问题都是np完全的。然后我们将WHEC问题化为整数线性规划(ILP)。因此,可以使用lp松弛法和舍入启发式方法得到近似解。我们的lp逼近算法产生的拥塞嵌入最多是最优解的两倍。最后,为了保证效率,我们开发了一种线性时间近似算法,该算法也提供了与lp近似相同的最坏情况近似界的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithms and complexity for weighted hypergraph embedding in a cycle
The problem of weighted hypergraph embedding in a cycle (WHEC) is to embed the weighted hyperedges of a hypergraph as the paths in a cycle, such that the maximum congestion of any physical link in the cycle is minimized. A simpler version of this problem is the weighted graph embedding in a cycle (WGEC) that embeds the weighted edges of a normal graph as the paths in a cycle. The WHEC and WGEC problems have applications in design automation, parallel computing and computer communication. In this paper we first show that both WHEC and WGEC problems are NP-Complete. Afterwards we formulate the WHEC problem as an integer linear programming (ILP). Therefore, an approximation solution can be obtained by using LP-relaxation and rounding heuristic. Our LP-approximation algorithm generates an embedding with congestion at most two times the optimal solution. Finally, to guarantee the efficiency, we develop a linear-time approximation algorithm that also provides a solution with the same worst case approximation bound as the LP-approximation.
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