Time-line based model for software project scheduling with genetic algorithms

Effective management of complex software projects depends on the ability to solve complex, subtle optimization problems. Most studies on software project management do not pay enough attention to difficult problems such as employee-to-task assignments, which require optimal schedules and careful use of resources. Commercial tools, such as Microsoft Project, assume that managers as users are capable of assigning tasks to employees to achieve the efficiency of resource utilization, while the project continually evolves. Our earlier work applied genetic algorithms (GAs) to these problems. This paper extends that work, introducing a new, richer model that is capable of more realistically simulating real-world situations. The new model is described along with a new GA that produces optimal or near-optimal schedules. Simulation results show that this new model enhances the ability of GA-based approaches, while providing decision support under more realistic conditions.