In this paper, an algorithm for solving the asymmetric traveling salesman problem is developed and tested by computation. This algorithm is based on the extension principle by Schoch and uses the assignment problem relaxation of the traveling salesman problem for computing lower bounds. Computational experience with randomly generated test problems indicate that the present algorithm yields good results in runtime which are comparable with the results of Smith/Srinivasan/Thompson. Computational experience are reported for up to 120-node problems with uniformly distributed and approximately normally distributed cost.