UC’s PhD in IEOR equips scholars to model, optimize, and control complex supply chains, healthcare operations, and service networks.
Mixed-integer model routing electric delivery fleets under range constraints
Digital twin of hospital OR scheduling minimizing patient wait times
Reinforcement-learning policy controlling warehouse AGV traffic
Network-flow optimization reducing food-bank distribution costs statewide
Robust inventory control under demand spikes in disaster relief supplies
Queueing analysis of 5 G edge-computing task offloading
Dynamic pricing algorithm balancing revenue and fairness on ride-share platforms
Monte-Carlo risk model for multi-tier semiconductor supply chains
Simulation of airport security lanes with social-distancing policies
Genetic algorithm scheduling wind-farm maintenance vessels
Heuristic optimizer for 3-D printing job batching in service bureaus
Blockchain smart-contract prototype for freight invoice reconciliation
Stochastic frontier analysis benchmarking energy-utility efficiency
AI explainability dashboard for workforce-scheduling fairness metrics
Multi-objective optimization of humanitarian logistics under uncertainty
Policy brief on resilience metrics for critical infrastructure networks
Citizen-science hackathon crowdsourcing bus-timetable improvements
White paper on algorithmic workforce management ethics
Workshop teaching linear programming with open-source solvers to NGOs
Conference on OR contributions to circular-economy transition
Optimize tomorrow’s systems with UC’s analytics-driven PhD.
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