Complexity and algorithms for Swap median and relation to other consensus problems

Luís Cunha, Thiago Lopes, Arnaud Mary
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Abstract

Genome rearrangements are events in which large blocks of DNA exchange pieces during evolution. The analysis of such events is a tool for understanding evolutionary genomics, based on finding the minimum number of rearrangements to transform one genome into another. In a general scenario, more than two genomes are considered and we have new challenges. The {\sc Median} problem consists in finding, given three permutations and a distance metric, a permutation $s$ that minimizes the sum of the distances between $s$ and each input. We study the {\sc median} problem over \emph{swap} distances in permutations, for which the computational complexity has been open for almost 20 years (Eriksen, \emph{Theor. Compt. Sci.}, 2007). We consider this problem through some branches. We associate median solutions and interval convex sets, where the concept of graph convexity inspires the following investigation: Does a median permutation belong to every shortest path between one of the pairs of input permutations? We are able to partially answer this question, and as a by-product we solve a long open problem by proving that the {\sc Swap Median} problem is NP-hard. Furthermore, using a similar approach, we show that the {\sc Closest} problem, which seeks to minimize the maximum distance between the solution and the input permutations, is NP-hard even considering three input permutations. This gives a sharp dichotomy into the P vs. NP-hard approaches, since considering two input permutations the problem is easily solvable and considering any number of input permutations it is known to be NP-hard since 2007 (Popov, \emph{Theor. Compt. Sci.}, 2007). In addition, we show that {\sc Swap Median} and {\sc Swap Closest} are APX-hard problems.
交换中值的复杂性和算法以及与其他共识问题的关系
基因组重排是大块 DNA 在进化过程中交换片段的事件。对这类事件的分析是理解基因组进化的一种工具,其基础是找到将一个基因组转变为另一个基因组的最少重排次数。在一般情况下,我们需要考虑两个以上的基因组,这就给我们带来了新的挑战。{/sc中值}问题包括:在给定三个排列和一个距离度量的情况下,找到一个排列$s$,使$s$和每个输入之间的距离之和最小。我们研究的是排列组合中{emph{swap}距离的{sc中值}问题,这个问题的计算复杂度问题已经有近20年的历史了(Eriksen, \emph{Theor. Compt. Sci.},2007)。我们通过一些分支来考虑这个问题。我们把中值解和区间凸集联系起来,其中图凸性的概念启发了下面的研究:中值突变是否属于输入突变对之间的每一条最短路径?我们能够部分地回答这个问题,作为副产品,我们通过证明{交换中值}问题是 NP-hard的,解决了一个长期悬而未决的问题。此外,我们还用类似的方法证明了{\sc Closest}问题(该问题旨在最小化解与输入排列组合之间的最大距离)即使考虑三个输入排列组合也是 NP 难的。这给出了P与NP-hard方法的截然对立,因为考虑两个输入排列组合,这个问题很容易求解,而考虑任意数量的输入排列组合,这个问题自2007年以来就被认为是NP-hard的(Popov, \emph{Theor. Compt.)此外,我们还证明了 {\scSwap Median} 和 {\scSwap Closest} 是 APX 难问题。
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