Real-Time Dispatch Optimization
A real-time mixed-integer-programming system that routes 200+ field technicians from live telemetry and work-scheduling data — improving emergency SLA from ~50% to 67%+.
Operations Research MIP Python Optimization
The challenge
Emergency response across a multi-state gas utility depends on getting the right technician to the right place fast — across 200+ field techs and constantly shifting conditions.
The system
A real-time mixed-integer-programming (MIP) optimizer integrating vehicle telemetry, the Banner customer-information system, and PragmaCAD work-scheduling data, with ball-tree spatial algorithms for fast nearest-resource matching.
Outcome
Emergency SLA improved from ~50% to 67%+.