Using Ant Algorithm to Find the Optimal Critical Path of a Projects Network

Intelligent techniques to solve the problem of decision-making in project management, apart from the methods of operations research, the choice was made on one of the algorithms of crowd intelligence represented by the Ant Colony Optimization algorithm (ACO)to solve the matter of finding the optimal critical path for the enterprise business network because the business network is more Networks tradition the behavior of the ant colony system to find the optimal critical path for the Critical Path Network(CPN) as. You own a project beginning contract (the first event) equivalent to an ant hill.The project end contract (the last event) is equivalent to the food site.The matter of finding the optimal critical path for the project is equivalent to the search process to find an optimal (the shortest) path between the nest and the food site.
The program ANTOCPN, written in Matlab language on a virtual business network. The program is featuring by its efficiency, accuracy of results, and the possibility of applying it to any business network, regard of the degree of complexity in terms of the number of paths (activities), whether real or imaginary, smoothly and easily. Also, the results of the ANTOCPN algorithm program were compared with the results of the genetic algorithm program for the same question GAOCPN for previous research, and the ant algorithm proved its worth in terms of speed in obtaining the optimal solution.