Blended selection in Ant Colony Optimization for solving Travelling Salesman Problem

TSP is one of the most well-known combinatorial optimization problems. Ant Colony optimization is highly recommended to solve discrete optimization problems whereas the selection strategy plays a crucial role in the performance of ACO while solving Travelling Salesman Problem (TSP). There are many selection strategies in ACO to solve TSP, such as roulette wheel selection, ranking selection and annealing selection etc. In ACO, the roulette wheel selection is primarily concerned with exploitation, whereas rank selection is influenced by exploration. Therefore, in this paper, a blend of both roulette wheel and ranking selection is proposed as a new selection strategy in ACO. The proposed selection method is tested over 12 standard TSP instances collected from TSP library TSPLIB. The best results obtained from the above mentioned selection method has been recorded and compared with other three selection methods. The experimental results show that the proposed selection method outperformed with other considered selection methods.