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Reconstruction Algorithms for Permutation Graphs and Distance-Hereditary Graphs

机译:置换图和距离遗传图的重构算法

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PREIMAGE CONSTRUCTION problem by Kratsch and Hemaspaandra naturally arose from the famous graph reconstruction conjecture. It deals with the algorithmic aspects of the conjecture. We present an O(n8) time algorithm for PREIMAGE CONSTRUCTION on permutation graphs and an O(n4(n + m)) time algorithm for PREIMAGE CONSTRUCTION on distance-hereditary graphs, where n is the number of graphs in the input, and m is the number of edges in a preimage. Since each graph of the input has n - 1 vertices and O(n2) edges, the input size is O(n3) (, or O(nm)). There are polynomial time isomorphism algorithms for permutation graphs and distance-hereditary graphs. However the number of permutation (distance-hereditary) graphs obtained by adding a vertex to a permutation (distance-hereditary) graph is generally exponentially large. Thus exhaustive checking of these graphs does not achieve any polynomial time algorithm. Therefore reducing the number of preimage candidates is the key point.
机译:Kratsch和Hemaspaandra的PREIMAGE CONSTRUCTION问题自然是由著名的图重构猜想引起的。它涉及猜想的算法方面。我们针对置换图提出O(n8)时间算法以进行PREIMAGE构建,并针对距离遗传图提出O(n4(n + m))时间算法以进行PREIMAGE构建,其中n是输入中图的数量,m是原像中的边缘数量。由于输入的每个图都有n-1个顶点和O(n2)边,因此输入大小为O(n3)(或O(nm))。对于置换图和距离遗传图,有多项式时间同构算法。然而,通过将顶点添加到排列(距离-遗传)图而获得的排列(距离-遗传)图的数量通常成指数地增加。因此,这些图的详尽检查无法实现任何多项式时间算法。因此,减少原像候选的数量是关键。

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