Considering that the business network is the most imitative network of the behavior (nature) of the ant colony system to find the optimal critical path in PERT networks because it has a project start node (first event) equivalent to the ant's home (nest), and a project end node (last event) equivalent to the food source (food). The problem of finding the optimal critical path for the project is equivalent to the search process to find the best (shortest) path between the nest and the food site. In this research, an ant colony optimization algorithm was proposed to find the critical path in PERT/CPM networks, and the proposed method was used to solve problems in construction projects, as this algorithm showed high efficiency in finding the critical path for project networks in record time compared to conventional solution methods and with the least number of iterations. To obtain clear graphics and high-resolution tables, the Ant Colony Optimization Program (ACOP) was applied, which was written in MATLAB on a virtual business network. The program is characterized by its efficiency and accuracy of its results and the possibility of applying it to any real and imaginary business network smoothly and easily. The results of the ACOP ant algorithm program were compared with the results of the genetic algorithm program for the same problem (GAOCPN) in a previously published research, and the ant algorithm proved its worth in terms of the speed of obtaining the optimal solution.