A memetic hunting search algorithm for the traveling salesman problem

Abstract

Since 1930s, traveling salesman problem is still one of the most studied problems in optimization. It started to be used as a benchmark for the new optimization methods that solves the combinatorial optimization problem NP-hard. This paper proposes an assessment of a memetic Hunting Search algorithm that uses a 2-Opt local search for solving the traveling salesman problem. Hunting Search is an evolutionary algorithm inspired by the method of group hunting of predatory animals. To show the quality of the memetic algorithm, it has been checked on a set of ten benchmark TSPLib instances and it outperforms the results obtained with previous Hunting Search algorithm.