A Multi-start Iterated Local Search Algorithm with Variable Degree of Perturbation for the Covering Salesman Problem

Abstract

The covering salesman problem (CSP) is a variant of the well-known traveling salesman problem (TSP), where there is no need to visit all the cities, but every city must be either visited or within a predetermined distance from at least one visited city in the tour. CSP, being a generalization of the TSP, is also NP-Hard. CSP finds important applications in emergency planning, disaster management, and rural healthcare. In this paper, we have proposed a multi-start iterated local search algorithm for the CSP. We also incorporated a variable degree of perturbation strategy to further improve the solution obtained through our approach. Computational results on a wide range of benchmark instances shows that our proposed approach is competitive with other state-of-the-art approaches for solving the CSP.