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Coloring Sparse Random k-Colorable Graphs in Polynomial Expected Time

机译:在多项式预期时间中着色稀疏随机k可色图

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Feige and Kilian showed that finding reasonable approximative solutions to the coloring problem on graphs is hard. This motivates the quest for algorithms that either solve the problem in most but not all cases, but are of polynomial time complexity, or that give a correct solution on all input graphs while guaranteeing a polynomial running time on average only. An algorithm of the first kind was suggested by Alon and Kahale in [1] for the following type of random k-colorable graphs: Construct a graph G_(n,p,k) on vertex set V of cardinality n by first partitioning V into k equally sized sets and then adding each edge between these sets with probability p independently from each other. Alon and Kahale showed that graphs from G_(n,p,k) can be k-colored in polynomial time with high probability as long as p ≥ c/n for some sufficiently large constant c. In this paper, we construct an algorithm with polynomial expected running time for k = 3 on the same type of graphs and for the same range of p. To obtain this result we modify the ideas developed by Alon and Kahale and combine them with techniques from semidefinite programming. The calculations carry over to general k.
机译:飞鸽和基利安表明,找到合理的近似解着色问题上的图表是很难的。这促使追求算法,无论是解决大多数但不是所有情况下的问题,但都是多项式时间复杂度,或者说所有的输入图形给出一个正确的解决方案,同时保证一个多项式运行时间只有平均。第一类的算法建议通过阿龙和Kahale在[1]以下类型的随机的k着色图的:构造一个图形G_(N,P,K)上的基数的顶点集V N乘第一分隔V输入ķ相等大小的组,然后加入这些组与从彼此概率p独立地之间的每个边缘。 ALON和Kahale表明从G_(N,P,K),该图形可以为k色以高概率在多项式时间只要为p≥C / N为一些足够大的常数c。在本文中,我们构建具有多项式预期运行时间上的相同类型的图表K = 3,并对于相同的范围p的算法。为了达到这个效果,我们修改由阿龙和Kahale所提出的想法,并与半定规划技术结合他们。计算结转到广义k。

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