The aim of this research is to compare traditional and modern methods to obtain the optimal solution using dynamic programming and intelligent algorithms to solve the problems of project management.
It shows the possible ways in which these problems can be addressed, drawing on a schedule of interrelated and sequential activities And clarifies the relationships between the activities to determine the beginning and end of each activity and determine the duration and cost of the total project and estimate the times used by each activity and determine the objectives sought by the project through planning, implementation and monitoring to maintain the budget assessed And not exceed them and often the most important of these goals is to reduce the time of implementation of the project to the minimum possible and then compare the plan and the reality and avoid the differences that occurred early, depending on the commitment to the scheduled schedule and the extent of implementation of each activity in time and cost without delay The main objective is to extract the critical path and divide the project into multiple stages using dynamic programming method, which helps to know when the project will be completed and to know the critical path in which the delay of any activity affects the duration of completion of the project The results are compared with the results of the artificial intelligence method and using the hybrid algorithm where the results are the same in both methods and the completion time of the project is (675) working days.