An Efficient Algorithm for Latin Squares in a Bipartite Min-Max-Plus System

TL;DR

This paper introduces a new, more efficient algorithm for computing eigenvalues and eigenvectors of Latin squares within bipartite min-max-plus systems, advancing computational methods in this mathematical domain.

Contribution

The paper presents a novel algorithm specifically designed for Latin squares in bipartite min-max-plus systems, improving efficiency over existing methods.

Findings

The new algorithm successfully computes eigenvalues and eigenvectors for Latin squares.

Comparison shows the proposed method outperforms existing algorithms in efficiency.

Illustrative examples demonstrate the algorithm's effectiveness.

Abstract

In this paper, we consider the eigenproblems for Latin squares in a bipartite min-max-plus system. The focus is upon developing a new algorithm to compute the eigenvalue and eigenvectors (trivial and non-trivial) for Latin squares in a bipartite min-max-plus system. We illustrate the algorithm using some examples. Furthermore, we compare the results of our algorithm with some of the existing algorithms which shows that the propose method is more efficient.