Mathematical Modeling of Resource-Constrained Project Scheduling Problem and Solving It by Using Metaheuristic Algorithms

One of the popular problems in operations research and project management is resource-constrained project scheduling problem. In the present study, this problem is modeled considering important goals consisted of minimization of the project completion time, as well as minimization of the maximum cost of the project in one day. In this regard, all the possible prerequisite relations between the activities of a project are considered. The proposed model has been implemented for three real projects in different sizes and by using metaheuristic algorithms including genetic algorithm, particle swarm optimization and differential evolution. The results showed that differential evolution and particle swarm optimization algorithms have efficient performances compared to the genetic algorithms for large- and medium-scale projects respectively. The use of metaheuristic algorithms for solving small-scale projects is not recommended.