The bat algorithm is a new swarm intelligence optimization algorithm. It has good optimization results in solving continuous domain optimization problems. However, its applications in the fields of discrete optimization are comparatively rare. We propose a discrete bat algorithm for solving the traveling salesman problem (TSP), and design related operators to realize the discretization of the algorithm. Reverse operation is also introduced to make the algorithm jump out of local optimal solutions. Comparative analysis on some classical examples from the TSPLIB shows that compared with the particle swarm optimization algorithm and the genetic algorithm, the proposed discrete bat algorithm has better solution quality and efficiency, which is an efficient optimization algorithm.