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Designing and implementing algorithms for the closest string problem

机译:最接近字符串问题的设计与实现算法

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摘要

Given a set of n strings of length L and a radius d, the closest string problem (CSP for short) asks for a string t(sol) that is within a Hamming distance of d to each of the given strings. It is known that the problem is NP-hard and its optimization version admits a polynomial time approximation scheme (PTAS). A number of parameterized algorithms have been then developed to solve the problem when d is small. Among them, the relatively new ones have not been implemented before and their performance in practice was unknown. In this study, we implement all of them by careful engineering. For those that have been implemented before, our implementation is much faster. For some of those that have not been implemented before, our experimental results show that there exist huge gaps between their theoretical and practical performances. We also design a new parameterized algorithm for the binary case of CSP. The algorithm is deterministic and runs in O (n(2)L + n(2)d. 6.16(d)) time, while the previously best deterministic algorithm runs in O (nL + nd(3). 6.731(d)) time. (C) 2018 Elsevier B.V. All rights reserved.
机译:给定一组长度L和半径D的N串,最接近的弦问题(简短的CSP)询问在D到给定字符串的每个汉明距离的字符串T(溶胶)。众所周知,问题是NP - 硬,其优化版本承认多项式时间近似方案(PTA)。然后,已经开发了许多参数化算法以解决D小时时解决问题。其中,相对较新的人之前尚未实施,其实践中的表现未知。在这项研究中,我们通过仔细的工程实施所有这些。对于以前实施的人,我们的实施更快。对于之前的一些尚未实施的人,我们的实验结果表明,它们之间存在巨大的差距与他们的理论和实际表现之间存在巨大差距。我们还为CSP的二进制情况设计了一种新的参数化算法。该算法是确定性的,在O(n(2)l + n(2)d中运行)。6.16(d))时间,而先前最佳的确定性算法在O(nl + nd(3)中运行。6.731(d))时间。 (c)2018年elestvier b.v.保留所有权利。

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