Logistics & Transport

Route optimization & demand forecasting

Client · Major last-mile delivery operator

Rebuilt route-optimization engine integrating demand forecasting, operational constraints and delivery windows — reducing cost per delivered parcel by 11%.

Challenge

Strong e-commerce growth with marked seasonality and hard-to-anticipate peaks (Black Friday, sales).
Route optimization based on simple heuristics, poorly adapted to modern constraints (2h slots, EVs, low-emission zones).
Chronic vehicle under-utilization on some routes and uncontrolled overtime on others.
Difficulty integrating last-minute drop-offs (returns, parcel shops).

Solution

Demand-forecast model at zip code × time slot × day, with weather, calendar and local events.
Hybrid optimization engine combining constraint programming (CP-SAT) and business heuristics — 200+ routes/day/depot in under 10 minutes.
Operational dashboard for site managers enabling simulation and manual fine-tuning.
Real-time re-routing module integrating disruptions during the day.

Business impact

−11% cost per delivered parcel on the pilot perimeter (3 depots, 18% of volume).
+6 pt vehicle fill rate.
+3 pt first-attempt delivery rate.
National rollout planned over 18 months (45 depots).

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