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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%+.