Best route optimization APIs for parcel delivery
- September 17, 2026
- 10 mins
Parcel delivery is one of the most demanding use cases in route optimization. High stop density, strict time windows, daily disruptions, constant cost pressure: last-mile operators have no room for error. Picking the wrong API can cost hours of manual rework every day, wiping out the theoretical gains of optimization altogether.
This article compares eleven route optimization APIs (Kardinal, Solvice, LogisticsOS, HERE, NextBillion AI, Google, GraphHopper, Timefold, Verso, Routific, Mapbox) on their ability to handle the real constraints of parcel delivery.
Key takeaways
What makes parcel delivery genuinely complex
Stop density
An urban delivery route typically groups 80 to 150 stops per driver per day. At that density, micro-decisions about sequencing have a direct impact on productivity: stop order, building access, repeat visits. Poor sequencing on a route that dense can waste 30 to 45 minutes per driver per day.
Time windows
Delivery slots, often one hour and sometimes thirty minutes, have become the e-commerce norm. A parcel delivered outside its window causes immediate customer dissatisfaction and usually a second attempt to arrange, which degrades profitability and service quality at the same time.
A plan that keeps moving all day
In parcel delivery, the morning plan rarely survives until noon. On the road, a parcel gets refused, a recipient is out, a pickup point is full, traffic jams up. At the depot, e-commerce orders keep arriving until mid-morning for same-day delivery. Both come down to the same thing: the plan changes constantly, and every change affects the rest of the route.
Without real-time re-optimization, meaning the engine's ability to recalculate the remaining routes and insert new stops into routes already under way without rebuilding them from scratch, the dispatcher has to step in manually, several times a day. Four solutions cover this capability in full: Kardinal, Timefold, NextBillion AI and Solvice.
Cost pressure
The last mile accounts for 40 to 50% of the total logistics cost of an order. With margins below 5% in most e-commerce segments, every unnecessary kilometer and every unoptimized working hour weighs directly on profitability.
The critical constraints for a parcel delivery API
Three levels of requirement shape the market: the classic base that everyone covers, the intermediate constraints that separate the good from the average, and the advanced constraints that genuinely make the difference in the field.
Distance and working time
The fundamental objectives of any optimization.
Covered by: All vendors except Mapbox.
Strict time windows
Handling of multiple or nested windows varies widely from one vendor to the next.
Covered by: All vendors.
Vehicle capacity
Weight, volume and custom limits per vehicle.
Covered by: All vendors.
Retry and premium parcels
Ranking the previous day's failed deliveries ahead of today's orders.
Covered by: All vendors except Mapbox.
Predictive traffic upstream
Expected traffic is factored in before optimization, not corrected afterwards.
Covered by: Kardinal, Solvice, GraphHopper, Google, HERE, Mapbox, NextBillion AI. Partial at LogisticsOS; absent at Routific, Timefold and Verso.
Mixed speed profiles
Car, bike and van within the same fleet.
Covered by: Kardinal, NextBillion AI, GraphHopper and HERE. Partial elsewhere.
Preferred zone assignment
Steering deliveries toward the courier who knows the area, without making it a hard rule.
Covered by: Kardinal, Timefold, Solvice, GraphHopper, HERE and LogisticsOS.
Workload balancing
Spreading working time fairly across couriers.
Covered by: Kardinal, Routific, NextBillion AI, Solvice, GraphHopper and LogisticsOS.
Real-time re-optimization
Automatic recalculation of the route during the day.
Covered by: Kardinal, Timefold, NextBillion AI and Solvice. Partial at Routific, Verso and LogisticsOS.
Lexicographic optimization
Ranking objectives instead of weighting them into a single formula, so multi-objective setups stay simple to configure and easy to explain.
Covered by: Kardinal and HERE only.
Route compactness
Keeping each route geographically tight and limiting overlap between couriers.
Covered by: Kardinal, Solvice and LogisticsOS only.
Zone-by-zone sequencing
Finishing one neighborhood before moving to the next.
Covered by: Kardinal, Solvice, GraphHopper and HERE.
Conditional return pickups
Only starting a return collection once the route is far enough along, without excessive rigidity.
Covered by: Kardinal and Solvice only.
Best-effort optional stops
Scheduling flexible-deadline parcels only when they fit without adding a vehicle.
Covered by: Kardinal, Timefold, NextBillion AI and Solvice.
Pickup-point anchoring
Forcing the service order around a pickup point (PUDO), a niche constraint.
Covered by: HERE only, ahead of Kardinal included.
Parcel delivery API comparison
Kardinal
95% coverage · 1st/11Kardinal remains the best-suited solution for parcel delivery, whatever the complexity segment. It is the only vendor to combine real-time re-optimization, route compactness, zone-by-zone sequencing and lexicographic optimization in a single offering.
Across all the constraints specific to this sector, Kardinal has only two gaps, both on niche needs: hourly cost that varies with the time of day, a morning-peak surcharge for instance, which only Solvice models, and tying stops to a pickup point, which only HERE offers.
Solvice
79% coverage · 2nd/11Solvice takes second place. It has one advantage Kardinal does not cover, modeling hourly cost according to the time of day, but it is a very niche need that only comes up in rare rate structures. It also joins Kardinal on conditional return pickups, a constraint these two solutions alone cover.
Solvice also fully covers real-time re-optimization, route compactness and zone-by-zone sequencing. Its limit: no lexicographic optimization. With a model that rich, balancing several objectives means setting a weight on each criterion, and the configuration quickly becomes a heavy machine to fine-tune.
LogisticsOS
77% coverage · 3rd/11LogisticsOS lands straight in third place, carried by its specialty: cost modeling. It is the only solution, alongside Kardinal on a neighboring axis, to cover flat-rate and overtime thresholds as well as optimizing the combined bill across own fleet and subcontractors. It also covers route compactness.
Its limits: real-time re-optimization and zone assignment are only partially covered.
HERE
73% coverage · 4th/11HERE surprises with two exclusives. It is the only solution besides Kardinal to offer lexicographic optimization, and the only one in the panel, Kardinal included, to cover pickup-point anchoring. It also leverages its mapping base for solid predictive traffic and complete speed profiles.
Its main weakness: real-time re-optimization is not covered, which penalizes it on operations with a high volume of daily disruptions.
NextBillion AI
68% coverage · 5th/11NextBillion AI remains solid on the fundamentals: predictive traffic, speed profiles, real-time re-optimization and best-effort optional stops are all covered. What it lacks is the finest layer: no route compactness, no zone-by-zone sequencing, no lexicographic optimization.
Google does not fully cover real-time re-optimization within this constraint scope, despite the quality of its mapping infrastructure. Predictive traffic and minimizing delays against a promised ETA remain strengths, but specialized speed profiles (bike, motorcycle) are absent, and no zone assignment is offered.
GraphHopper
52% coverage · 7th/11GraphHopper holds its position thanks to its mixed speed profiles and zone-by-zone sequencing, two points where it joins Kardinal, Solvice and HERE. It covers neither real-time re-optimization, nor lexicographic optimization, nor optional stops.
Timefold
48% coverage · 8th/11Timefold surprises by fully covering real-time re-optimization and best-effort optional stops, two advanced constraints where it joins Kardinal. But it has no predictive traffic, and its coverage of the basic constraints lags behind the more generalist vendors.
Verso, Routific and Mapbox
44% · 38% · 26%These three solutions hit their limits as soon as a fleet exceeds about ten vehicles or operations require fine-grained disruption handling.
- Verso (44%) stays limited to basic operations, without complete real-time re-optimization.
- Routific (38%) covers the fundamentals but lacks most advanced capabilities.
- Mapbox (26%) benefits from good predictive traffic thanks to its mapping base, but remains above all a visualization tool rather than a genuine route optimizer.
Summary table
Our verdict
Fleet size is not what should drive the choice. What matters is how far your operation goes beyond the classic constraints. Start from the five solutions that clear the bar for parcel delivery, then narrow the list according to your needs.
