Comparison and analysis of solving travelling salesman problem using GA, ACO and hybrid of ACO with GA and CS

The Travelling Salesman Problem (TSP) is a very popular combinatorial optimization problem of real world. The objective is to find out a shortest possible path travelled by a salesman while visited every city once and returned to the origin city. TSP is one of the NP hard problems and several attempts have been done to solve it by traditional methods. Computational methods give better solution for TSP as most of them are based on repetitive learning. In the proposed paper four optimization techniques are presented such as ant colony optimization (ACO), genetic algorithm (GA), hybrid technique of ant colony optimization (ACO) and genetic algorithm (GA) and hybrid technique of ant colony optimization (ACO) and cuckoo search (CS) algorithm is proposed and implemented for travelling salesman problem. The result shows that shortest efficient tour is obtained by new hybrid algorithm.