An Ant Colony Optimization and Bayesian Network Structure Application for the Asymmetric Traveling Salesman Problem

The asymmetric traveling salesman problem (ATSP) is an NP-hard problem. The Bayesian network structure which describes conditional independence among subsets of variables is useful in reasoning uncertainty. The ATSP is formed as the Bayesian network structure and solved by the ant colony optimization (ACO) in this study. The proposed algorithm is tested in different sample size. The exam case is finding customer preference's city sequence. Results show the proposed algorithm has a higher joint probability than random selected case. More applications such as the sequential decision, the variable ordering or the route planning can also implement.