We solve the recognition problem (RP) for the class of Demidenko matrices. Our result closes a remarkable gap in the recognition of specially structured matrices. Indeed, the recognition of permuted Demidenko matrices is a longstanding open problem, in contrast to the effciently solved RP for important subclasses of Demidenko matrices such as the Kalmanson matrices, the Supnick matrices, the Monge matrices and the Anti-Robinson matrices. The recognition of the permuted Demidenko matrices is relevant in the context of hard combinatorial optimization problems which become tractable if the input is a Demidenko matrix. Demidenko matrices were introduced by Demidenko in 1976, when he proved that the Travelling Salesman Problem (TSP) is polynomially solvable if the symmetric distance matrix fulfills certain combinatorial conditions, nowadays known as the Demidenko conditions. In the context of the TSP the recognition problem consists in deciding whether there is a renumbering of the cities such that the correspondingly renumbered distance matrix fulfills the Demidenko conditions, thus resulting in a polynomially solvable special case of the TSP. We show that such a renumbering of n cities can be found in $O(n^4)$ time, if it exists.
翻译:我们解决了Demidenko 矩阵的识别问题(RP ) 。 我们的结果弥补了在识别特殊结构矩阵方面存在的显著差距。 事实上,对Meded Demidenko 矩阵的识别是一个长期的开放问题,而对于Demidenko 矩阵的重要子类,如Kalmanson矩阵、Supnick矩阵、Monge矩阵和反Robinson矩阵,我们解决了识别问题(RP ) 。对Mendendienko 矩阵的识别与硬组合优化问题相关,如果输入为Demidenko 矩阵,这种组合优化问题就变得可移植。 Demidenko 矩阵是1976年由Demidenko 引入的,当时Demidenko 矩阵证明,如果对称远程矩阵满足了某些组合条件(现称为Demidenko 条件 ), 则该矩阵是多元销售员问题(TSP) 的多元软软体软体软体软体软体的。 在 TSP 4 中, 特别的大小城市中可以找到相应的重新编号 。