A simplex-like method to compute the eigenvalue of an irreducible (max,+)-system

In this paper, we present an alternative method to compute the eigenvalue of an irreducible (max,+)-system. The method resembles the well-known simplex method in linear programming in the sense that the eigenvalue and a corresponding eigenvector are obtained by going along the boundary of a polygon-like set, while increasing the number of equalities in some (max,+)-algebraic eigenvalue–eigenvector expression, until only equalities are left over. The latter is unlike the normal linear programming approach where, going along the boundary of a polygon-like set, a linear functional is optimized.