arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1702.05710cs.DScs.AI
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顶点分离极小化问题的多项式时间高效构造启发式算法

Polynomial Time Efficient Construction Heuristics for Vertex Separation Minimization Problem

Pallavi Jain, Gur Saran, Kamal Srivastava

摘要:

顶点分离最小化问题(VSMP)是指在一个图G =(V,E)中,寻找一个使最大顶点割或顶点分离最小的布局。这是一个NP完全问题,一般可以应用元启发式技术来找到近似最优解。VSMP在超大规模集成电路设计、图形绘制和计算机语言编译器设计中有应用。VSMP对于网格、树、置换图和余图都是多项式可解的。构造算法在元启发式算法中起着非常重要的作用,因为它们负责生成初始解,从而导致快速收敛。本文提出了三种构造算法H1、H2和H3,并在网格、小图、树和Harwell Boeing图上进行了实验,共248个图的实例。实验结果表明,H1,H2和H3能够达到最好的结果分别为88.71%,43.5%和37.1%的总的实例,而文献中的最佳构造启发式算法达到最好的解决方案的总的实例的39.9%。我们还比较了结果与国家的最先进的元启发式GVNS,并观察到,建议的建设misticistics提高了一些输入实例的结果。结果发现,GVNS获得最好的结果为82.9%的所有输入实例的实例和启发式H1获得最好的结果为82.3%的所有输入实例。

英文摘要:

Vertex Separation Minimization Problem (VSMP) consists of finding a layout of a graph G = (V,E) which minimizes the maximum vertex cut or separation of a layout. It is an NP-complete problem in general for which metaheuristic techniques can be applied to find near optimal solution. VSMP has applications in VLSI design, graph drawing and computer language compiler design. VSMP is polynomially solvable for grids, trees, permutation graphs and cographs. Construction heuristics play a very important role in the metaheuristic techniques as they are responsible for generating initial solutions which lead to fast convergence. In this paper, we have proposed three construction heuristics H1, H2 and H3 and performed experiments on Grids, Small graphs, Trees and Harwell Boeing graphs, totaling 248 instances of graphs. Experiments reveal that H1, H2 and H3 are able to achieve best results for 88.71%, 43.5% and 37.1% of the total instances respectively while the best construction heuristic in the literature achieves the best solution for 39.9% of the total instances. We have also compared the results with the state-of-the-art metaheuristic GVNS and observed that the proposed construction heuristics improves the results for some of the input instances. It was found that GVNS obtained best results for 82.9% instances of all input instances and the heuristic H1 obtained best results for 82.3% of all input instances.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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