Branch-and-cut algorithms for the covering salesman problem

The Covering Salesman Problem (CSP) is a generalization of the Traveling in which tour not required to visit all vertices, as long vertices are covered by tour. objective CSP find minimum length Hamiltonian cycle over subset that covers an undirected graph. In this paper, valid inequalities from generalized traveling salesman problem applied addition new explore distinct aspects problem. A branch-and-cut framework assembles exact and heuristic separation routines for integer fractional solutions. Computational experiments show proposed outperformed methodologies literature with respect optimality gaps. Moreover, optimal solutions were proven several previously unsolved instances.