Application of Three Meta-Heuristic Algorithms for Maximizing the Net Present Value of a Resource-Constrained Project Scheduling Problem with Respect to Delay Penalties

The Resource Constrained Project Scheduling Problem (RCPSP) is been studied under different kinds of constraints and limitations. In this paper, we are going to consider the discounted cash flows for project activities, and delay penalties which occur when the project make span exceeds its deadline as the objective function of the RCPSP. To solve the model, we will take advantage of three different meta-heuristic algorithms - Genetic Algorithm (GA), Imperialist Competitive Algorithm (ICA), and Shuffled Frog Leaping Algorithm (SFLA) - to achieve the optimal solution of the problem. The evaluation of the algorithms performance reveals that, in comparison with ICA and SFLA, GA performs better, especially in large-scale problems.