Experimental study of a hybrid genetic algorithm for the multiple travelling salesman problem

The multiple travelling salesman problem (MTSP), an extension of the well-known travelling salesman problem (TSP), is studied
here. In MTSP, starting from a depot, multiple salesmen require to visit all cities so that each city is required to be visited only once
by one salesman only. It is NP-hard and is more complex than the usual TSP. So, exact optimal solutions can be obtained for
smaller sized problem instances only. For large-sized problem instances, it is essential to apply heuristic algorithms, and amongst
them, genetic algorithm is identified to be successfully deal with such complex optimization problems. So, we propose a hybrid
genetic algorithm (HGA) that uses sequential constructive crossover, a local search approach along with an immigration
technique to find high-quality solution to the MTSP. /en our proposed HGA is compared against some state-of-the-art al-
gorithms by solving some TSPLIB symmetric instances of several sizes with various number of salesmen. Our experimental
investigation demonstrates that the HGA is one of the best algorithms