PhD Thesis Proposal: Prabhat Hegde

"Optimizing Complex Systems Involving Stakeholder Feedback: Applications to transportation and coastal adaptation planning"

Abstract

Many complex systems operate within a cyclic decision-making structure, where a centralized planner makes initial decisions based on available information and must account for how these decisions will influence, and be influenced by, constituent responses. This feedback loop refines strategies over time, balancing trade-offs, evolving system conditions, and stakeholder priorities. This thesis examines two applications of such systems: school bus routing and scheduling, and coastal adaptation planning.

Excessively long school bus rides can negatively impact student performance and well-being. These challenges are particularly pronounced in rural school districts due to students from different schools sharing trips, irregular road networks, and drop-off-induced traffic congestion. To address these issues, this thesis formulates a mixed-load school bus routing problem aimed at minimizing student travel time and develops a novel cluster-and-route heuristic to solve this problem in reasonable time. Additionally, we model an iterative feedback mechanism, where student ridership decisions respond to routing strategies designed by a route planner, capturing the dynamic interplay between mode choice and congestion in the vicinity of the schools.

A similar feedback-driven dynamic exists in coastal adaptation planning. Shoreline communities increasingly face the challenge of combating erosion and flooding while sustaining economic activity. Increasingly, research suggests that managed retreat may be a necessary intervention in some of these communities. However, there is little research on whether managed retreat better balances multiple planning objectives than continued beach nourishment. This thesis addresses this gap by developing a framework to identify optimal nourishment and retreat trigger timings under uncertainty. By explicitly modeling the effects of adaptation actions on observable state variables—such as beach width and aggregate property valuation—we capture how these changes influence decision-making over the entirety of the planning time horizon.

Both projects improve decision making in complex systems: in the school bus routing application, results indicate a 38–39% improvement in student travel time to school; and in the beach nourishment application, modeling suggests managed retreat 20 years earlier than existing benchmarks when accounting for uncertainty and balancing multiple objectives. Through integer programming and feedback-informed adjustments, this thesis provides insights into optimizing resource allocation and decision-making in complex systems.

Thesis Committee

• Prof. Vikrant Vaze (Chair)
• Prof. Klaus Keller (Co-chair)
• Prof. Geoff Parker

Contact

For more information, contact Thayer Registrar at thayer.registrar@dartmouth.edu.