| dc.description.abstract | Veritas Corporation is a thriving company in the fast-paced telecommunications industry. To keep up with the dynamic industry, a significant quantity of projects must be scheduled in a short time period without impacting each other. While Veritas succeeds in this, they do so at the cost of a significant number of management hours. The objective of this research is to produce a quantitative method to quickly and accurately produce an optimized schedule for the vast number of projects that Veritas implements. This was accomplished by making iterative binary integer linear programming models. The first model was to serve as a proof of concept and was conducted on a small market. After successful completion, the model was expanded to a larger market and verified. Outstanding results were seen in both iterations. By using historical data, it is evident that the optimized model outperformed traditional manual scheduling. The larger and more complicated the situation became the greater the improvement provided by the optimized model. | |
