This paper presents a new approach to solve the Software Project Scheduling Problem. This problem is NP-hard and consists in finding a workertask schedule that minimizes cost and duration for the whole project, so that task precedence and resource constraints are satisfied. Such a problem is solved with an Ant Colony Optimization algorithm by using the Max–Min Ant System and the Hyper-Cube framework. We illustrate experimental results and compare with other techniques demonstrating the feasibility and robustness of the approach, while reaching competitive solutions.