arXivDaily arXiv每日学术速递 周一至周五更新
北美退伍军人节(Veterans Day),12 日无更新
arXiv 1208.0954cs.CC
收藏

P = NP

P = NP

Sergey V. Yakhontov

摘要:

本文证明了P=NP。证明,在这项工作中,是一个建设性的:程序的多项式时间确定性多带图灵机M_MistsAcceptingPath,确定是否存在一个接受的计算路径的多项式时间非确定性单带图灵机M_NP,被构造(机器M_MistsAcceptingPath是不同的每个图灵机M_NP)。机器M_ProstsAcceptingPath基于问题LP(线性规划)的简化,而不是通常使用的问题3-CNF-SAT的简化。更详细地说,机器M_AcceptingPath将初始字符串问题简化为另一个字符串问题TCPE(在论文中定义),该问题是NP完全的,并且在多项式时间内可判定。机器M_NP的时间复杂度是O(t(n)^{272}),其中t(n)是机器M_NP的时间复杂度的上界。

英文摘要:

The present work proves that P=NP. The proof, presented in this work, is a constructive one: the program of a polynomial time deterministic multi-tape Turing machine M_ExistsAcceptingPath, that determines if there exists an accepting computational path of a polynomial time non-deterministic single-tape Turing machine M_NP, is constructed (machine M_ExistsAcceptingPath is different for each Turing machine M_NP). Machine M_ExistsAcceptingPath is based on reduction to problem LP (linear programming) instead of reduction to problem 3-CNF-SAT which is commonly used. In more detail, machine M_AcceptingPath uses a reduction of the initial string problem to another string problem TCPE (defined in the paper) that is NP-complete and decidable in polynomial time. The time complexity of machine M_ExistsAcceptingPath is O(t(n)^{272}) wherein t(n) is an upper bound of the time complexity of machine M_NP.

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。

↑