Two industrial engineering graduate students, Michael Williams (engineering management) and Jordan Ticktin (industrial engineering) presented at the 2019 INFORMS Annual Meeting. More than 6,000 INFORMS members, students and academic and industry experts attended the meeting in Seattle, WA, October 20-23. INFORMS is the world’s largest professional association dedicated to and promoting best practices and advances in operations research, management science, and analytics to improve operational processes, decision-making and outcomes.
Williams presented the poster “Optimal Payment Policies and Resource-Constrained Project Scheduling with Discounted Cash Flows: The Contractor’s Perspective.” In this work he used Constraint Programming, a technique from computational optimization, to quantify the impact of different payment plans on the contractor’s profit when optimally scheduling his project. He observed notable potential profit losses when choosing the wrong payment plan which suggests a careful analysis before negotiating contracts in practice.
Ticktin (above) presented his thesis “Intra-Project Learning in Resource-Constrained Project Scheduling.” He studied the effect of autonomous learning when scheduling projects with multiple limited resources. The resulting novel combinatorial problems are extremely hard to solve and the development of sophisticated optimization approaches based on Constraint Programming was necessary in order to provide good results for large projects with 120 tasks. After the experimentation with more than a hundred thousand scenarios, it turned out that the integration of learning features into the project scheduling process can dramatically reduce the overall project duration. The project has been carried out in collaboration with researchers from China and Colorado and the detailed findings will be submitted for publication soon.
Alessandro Hill is the faculty advisor for both projects.
