A Comparative Study of Three Nature-Inspired Algorithms Using the Euclidean Travelling Salesman Problem

Recently, the nature has become a source of inspiration for the creation of many algorithms. A great research effort has been devoted to the development of new metaheuristics, especially nature-inspired one to solve numerous difficult combinatorial problems appearing in various industrial, economic, and scientific domains. The nature-inspired algorithms offer additional advantages over classical algorithms; they seek to find acceptable results within a reasonable time, rather than an ability to guarantee the optimal or sub-optimal solution. The travelling salesman problem (TSP) is an important issue in the class of combinatorial optimization problem and also classified as NP-hard problem and no polynomial time algorithm is known to solve it. Based on three nature-inspired algorithms, this paper proposes a comparative study to solve TSP. The proposed algorithms are evaluated on a set of symmetric benchmark instances from the TSPLIB library.