```json { "title": "Best route optimization APIs for retail & distribution", "url": "https://kardinal.ai/best-route-optimization-api-retail-distribution/", "datePublished": "2026-09-18", "dateModified": "2026-09-25", "language": "en-GB", "description": "A comparison of the 11 best route optimization APIs for retail & distribution, benchmarked against constraints representative of the market.", "author": "Kardinal", "publisher": "Kardinal" } ``` # Best route optimization APIs for retail & distribution # Best route optimization APIs for retail & distribution > **In short:** Among route optimization APIs for retail & distribution, Kardinal dominates this sector ranking by a wide margin. Its only real gap concerns synchronising two resources for cross-docking, one specific use case covered solely by Solvice. - **11** APIs compared in this sector - **97%** of retail & distribution constraints covered by Kardinal, ranked 1st - **82%** LogisticsOS, the closest competitor - **Premium > 70%:** Kardinal (97%), LogisticsOS (82%), Solvice (78%), HERE (73%), Google (71%). - **Standard 50-70%:** NextBillion AI (66%), GraphHopper (53%). - **Basic < 50%:** Timefold (47%), Verso (43%), Routific (38%), Mapbox (28%). Retail and distribution impose a constraint few other sectors stack to this degree: every store has its own receiving windows, its own hierarchy of subcontracted carriers, and its own history of non-compliance to avoid. An optimizer that treats every store the same way produces schedules store teams reject on the ground. This article compares eleven route optimization APIs (Kardinal, LogisticsOS, Solvice, HERE, Google, NextBillion AI, GraphHopper, Timefold, Verso, Routific, Mapbox) on their ability to handle the specific constraints of retail and distribution. > **A sector analysis, drawn from the full benchmark.** For a market-wide view across all solutions and all sectors: [the main guide to route optimization APIs](https://kardinal.ai/best-route-optimization-api/). The raw data sits in the [2026 benchmark](https://kardinal.ai/benchmark-route-optimization-api-2026/), and the price lists in the [pricing comparison](https://kardinal.ai/route-optimization-api-pricing-2026-comparison/). ## Key takeaways 1. In this sector, **Kardinal covers 97% of the relevant constraints**. LogisticsOS follows (82%), then Solvice (78%), HERE (73%) and Google (71%). 2. **Ranking subcontracted carriers by store**, useful for honouring different framework agreements from one store to the next, is fully covered only by Kardinal. 3. Kardinal has only **one real gap** in this sector: synchronising two resources for cross-docking, one specific use case, covered solely by Solvice. 4. **Lexicographic optimization**, which ranks objectives rather than weighting them, is only available from Kardinal and HERE. The others fall back on a weight for every criterion, which quickly turns into a sprawling setup to fine-tune. Ranking keeps multi-objective optimization simple and readable. ## What makes retail & distribution genuinely complex ### Receiving windows specific to each store Every store sets its own receiving hours, sometimes with slots that change by day of the week. A truck that arrives outside its window can be turned away at the dock, invalidating the whole route behind it. ### A hierarchy of subcontracted carriers Distribution chains often work with several subcontracted carriers under different framework agreements by store or region. The optimizer has to honour a preference order between carriers, rather than settling for a binary choice between own fleet and subcontracting. ### Non-compliance to avoid Some stores have a history of disputes with certain carriers or certain vehicle types: a dock too narrow for a semi-trailer, a past contractual dispute. The optimizer has to be able to exclude these combinations rather than discover them in the field. ### Multi-depot rotations Distribution networks often rely on several regional warehouses. Every store has to be served from the most relevant depot, without the optimizer sending a truck across an entire region for a single delivery. ### Cross-docking between routes Some distribution flows pass through a transfer point where one resource drops a load that another picks up to carry it further. The two movements have to be synchronized in time. ## The critical constraints for a retail & distribution API Three levels of requirement structure the market: the classic baseline everyone covers, the intermediate constraints that are indispensable in practice, and the advanced constraints that genuinely make the difference in distribution. **Classic (3)** - **Receiving windows by store** — Every store sets its own hours. Covered by: every vendor. - **Delivery from a regional depot** — The core movement of the business. Covered by: every vendor. - **Capacity and load compatibility by store** — Adapting the load to each store's constraints. Covered by: every vendor except Mapbox. **Intermediate (4)** - **Choice between own fleet and subcontracting** — Arbitrating between internal and external resources based on cost or availability. Covered by: Kardinal, Solvice, LogisticsOS, Google, HERE and NextBillion AI. Partial at GraphHopper. - **Several regional depots** — Serving each store from the most relevant depot. Covered by: every vendor except Routific and Mapbox. - **Excluding store/carrier combinations** — Avoiding known non-compliances. Covered by: Kardinal, Solvice, LogisticsOS, Google and HERE. Absent at GraphHopper, Mapbox, Routific, Timefold and Verso. - **Predictive traffic** — Expected traffic is factored in before optimization, not corrected afterwards. Covered by: Kardinal, Solvice, GraphHopper, Google, HERE, Mapbox and NextBillion AI. Absent at Routific, Timefold and Verso. **Advanced (4)** - **Ranking subcontracted carriers by store** — Honouring a preference order between carriers under different framework agreements by store. Covered by: Kardinal only. Partial at Solvice and LogisticsOS. - **Lexicographic optimization** — First meeting receiving windows, then minimizing costs, with no weights to calibrate between the two. Covered by: Kardinal and HERE only. - **Route compactness** — Keeping each route geographically tight across stores in the same area. Covered by: Kardinal, Solvice and LogisticsOS only. - **Two-resource synchronization (cross-docking)** — Time-coupling the drop of a load and its pickup by another resource. Covered by: Solvice only, ahead of Kardinal. ## The retail & distribution APIs compared ### Kardinal — the most complete API for retail & distribution (97% coverage · 1st/11) Kardinal is the most complete solution for retail distribution. It is the only vendor to fully cover ranking subcontracted carriers by store, a key point for honouring different framework agreements from one store to the next, and it also combines lexicographic optimization and route compactness. Its only real gap in this sector: synchronising two resources for cross-docking, one specific use case, covered solely by Solvice. **Ideal for:** Distribution chains of every size, from regional multi-depot networks to large multi-carrier chains with differentiated framework agreements by store. ### LogisticsOS — built around cost trade-offs (82% coverage · 2nd/11) LogisticsOS comes in second, carried by its cost modelling. It covers the choice between own fleet and subcontracting well, along with partial carrier ranking. **Ideal for:** Operators constantly arbitrating between in-house fleet and subcontracting on economic grounds. ### Solvice — the only one to synchronize cross-docking (78% coverage · 3rd/11) Solvice takes third place. It covers the only constraint in this sector that Kardinal lacks: two-resource synchronization for cross-docking. It also joins Kardinal on route compactness and excluding store/carrier combinations. 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. **Ideal for:** Operators for whom cross-docking between several routes or carriers is central, and who have the resources to tune weights criterion by criterion. ### HERE — strict priority ranking (73% coverage · 4th/11) HERE is the only solution besides Kardinal to offer lexicographic optimization, and covers excluding store/carrier combinations well. Its limit: no route compactness, no carrier ranking by store. **Ideal for:** Operators who want to rank their priorities strictly and already run the HERE mapping ecosystem. ### Google — strong mapping, advanced constraints absent (71% coverage · 5th/11) Google covers the fundamentals well: receiving windows, multiple depots, excluding combinations. But none of the sector's four advanced constraints are covered, even partially. **Ideal for:** Distribution networks with standard needs, with no complex carrier ranking and no cross-docking. ### NextBillion AI — solid on the fundamentals, behind on advanced (66% coverage · 6th/11) NextBillion AI covers the own-fleet/subcontracting choice and predictive traffic well, but none of the sector's advanced constraints are covered. **Ideal for:** High-volume operators with standard multi-depot distribution needs. ### GraphHopper, Timefold, Verso, Routific and Mapbox — insufficient coverage for professional retail (53% → 28%) - **GraphHopper (53%)** covers predictive traffic and multiple depots, but neither excluding combinations nor advanced constraints. It remains suited to small networks. - **Timefold (47%)** and **Verso (43%)** lag on most of the sector's fundamentals. - **Routific (38%)** and **Mapbox (28%)** are not designed for professional retail distribution. ## Summary table | Solution | Coverage | Carrier ranking | Excluding combinations | Route compactness | Lexicographic | |---|---|---|---|---|---| | Kardinal | 97% | Full | Full | Full | Full | | LogisticsOS | 82% | Partial | Full | Full | No | | Solvice | 78% | Partial | Full | Full | No | | HERE | 73% | No | Full | No | Full | | Google | 71% | No | Full | No | No | | NextBillion AI | 66% | No | No | No | No | | GraphHopper | 53% | No | No | No | No | | Timefold | 47% | No | No | No | No | | Verso | 43% | No | No | No | No | | Routific | 38% | No | No | No | No | | Mapbox | 28% | No | No | No | No | ## Our verdict Network size is not what should drive the choice. What matters is how much of your constraints go beyond the classic fundamentals. Start from the five leading solutions on retail & distribution, then narrow the list according to your needs. **Starting point · the top 5** Kardinal, LogisticsOS, Solvice, HERE and Google all cover the fundamentals of retail distribution well. Kardinal leads the group by 15 points. **You exclude store/carrier combinations** No solution in the top 5 drops out at this stage, they all cover it at least partially. **You need to rank subcontracted carriers by store** Google and HERE, which don't cover this point, drop out. Kardinal, LogisticsOS and Solvice remain, and only Kardinal covers it in full, handles route compactness alongside Solvice and LogisticsOS, and ranks its objectives without a stack of weights. **And on price** Among the top 5, Kardinal is also the most competitive overall, including for mid-size networks. The details are in our [2026 pricing comparison](https://kardinal.ai/route-optimization-api-pricing-2026-comparison/). ## Running a retail network with several subcontracted carriers and regional depots? Test Kardinal optimization on your own data, with no commitment. **[Start with the free tier →](https://console.kardinal.ai/)** · **[Read the documentation](https://developers.kardinal.ai/)** · **[See the full benchmark](https://kardinal.ai/benchmark-route-optimization-api-2026/)** ## FAQ ### Which route optimization API should you choose for retail and distribution? Kardinal is the most complete solution, with 97% sector coverage, and the most competitive on price among the top 5. LogisticsOS (82%) and Solvice (78%) follow, ahead of HERE (73%) and Google (71%). If you need to rank subcontracted carriers by store, the shortlist narrows to Kardinal, LogisticsOS and Solvice. ### How do you manage several subcontracted carriers with different framework agreements by store? This ranking lets the optimizer honour a preference order between carriers based on the store, rather than settling for a binary choice between own fleet and subcontracting. Kardinal is the only solution in the panel to cover it in full; Solvice and LogisticsOS cover it only partially. ### How do you avoid sending the wrong carrier or vehicle to a store? Excluding store/carrier combinations lets you rule out associations known to be non-compliant: a dock too narrow for a semi-trailer, a past contractual dispute. Kardinal, Solvice, LogisticsOS, Google and HERE cover this constraint. ### What is cross-docking and which API supports it in distribution? Cross-docking means having one resource drop a load at a warehouse, then having another resource pick it up in the same flow to carry it further. The two movements must be synchronized in time. Solvice is the only solution in the panel to offer this synchronization, ahead of Kardinal. ### How do you optimize a distribution network with several regional depots? The optimizer has to be able to serve each store from the most relevant depot rather than fixing a rigid assignment. Every solution in the panel covers this basic constraint, except Routific and Mapbox. ## Going further - [Oversized & heavy freight](https://kardinal.ai/best-route-optimization-api-oversized-heavy-freight/) — Matched crews and equipment, bulky returns and regional depot networks: the constraints of heavy freight. - [Parcel delivery](https://kardinal.ai/best-route-optimization-api-parcel-delivery/) — Stop density, strict time windows and daily disruptions: the constraints that separate the APIs on the last mile. - [Long-haul / FTL](https://kardinal.ai/best-route-optimization-api-long-haul-transport/) — Regulation, driving hours and rate modeling on full truckload.