Enhancing Project Management through Integration of PERT, Monte Carlo Simulation, and DBSCAN

Document Type : Original Article


Faculty of Management and Accounting, Karaj Branch, Islamic Azad University, Karaj, Iran.


In this article, according to the projects that have definite definite activities, but there is no definite point of view in terms of time for the implementation of the activities, and due to the necessity of using random samples in the simulation of the PERT schedule from the Monte Carlo simulation environment for production The schedule was used in a state where the times have uncertainty, and then according to the number of schedule production based on the number production standard from the data mining approach of the supervised data with labels based on three optimistic, probable and pessimistic situations, the data by algorithm NSGA-III artificial intelligence was processed based on the DBSCAB approach To optimize the multiple categories that have been created and create data permutations correctly and intelligently. The subject investigated in the section on finding the optimal answer in finding the center of the data crowd is the use of artificial intelligence NSGA-III to examine the center and radius of the data and create the possibility of creating supervised clusters and obtain the most optimal classification


Main Subjects