Recognising permuted Demidenko matrices

TL;DR

This paper addresses the longstanding open problem of recognizing permuted Demidenko matrices, providing an efficient $O(n^4)$ algorithm that has implications for solving certain instances of the Traveling Salesman Problem.

Contribution

We present the first polynomial-time algorithm for recognizing permuted Demidenko matrices, closing a significant gap in structured matrix recognition.

Findings

Recognition of permuted Demidenko matrices can be achieved in $O(n^4)$ time.

The result enables polynomial-time solutions for specific TSP instances.

The work extends the understanding of structured matrices in combinatorial optimization.

Abstract

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.