双保留字符串映射的局部搜索2.917-近似算法
A local search 2.917-approximation algorithm for duo-preservation string mapping
摘要：
本文研究了{ \em最大双保留字符串映射}（{ \sc Max-Duo}）问题，它是已有研究的{ \em最小公共字符串划分}（{ \sc MCSP}）问题的补充.这两个问题在许多领域都有应用，包括文本压缩和生物信息学。受早期局部搜索算法的启发，我们提出了一种改进的近似，并表明其性能比不大于${35}/{12} < 2.917$。这优于{ \sc Max-Duo}的当前最佳$3.25$近似。我们的算法的性能分析是通过一个复杂而有趣的摊销。我们的算法的局部间隙的两个下界也提供了。
英文摘要：
We study the {\em maximum duo-preservation string mapping} ({\sc Max-Duo}) problem, which is the complement of the well studied {\em minimum common string partition} ({\sc MCSP}) problem. Both problems have applications in many fields including text compression and bioinformatics. Motivated by an earlier local search algorithm, we present an improved approximation and show that its performance ratio is no greater than ${35}/{12} < 2.917$. This beats the current best $3.25$-approximation for {\sc Max-Duo}. The performance analysis of our algorithm is done through a complex yet interesting amortization. Two lower bounds on the locality gap of our algorithm are also provided.
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。
