An Improved Unordered Pair Bat Algorithm for Solving the Symmetrical Traveling Salesman Problem

Bat algorithm is an effective swarm intelligence optimization algorithm which is widely used to solve continuous optimization problems. But it still has some limitations in search process and can't solve discrete optimization problems directly. Therefore, this paper introduces an unordered pair and proposes an unordered pair bat algorithm (UPBA) to make it more suitable for solving symmetric discrete traveling salesman problems. To verify the effectiveness of this method, the algorithm has been tested on 23 symmetric benchmarks and compared its performance with other algorithms. The results have shown that the proposed UPBA outperforms all the other alternatives significantly in most cases.