Ask a quantum vendor which industry they can help first and many will say logistics. Routing, scheduling and loading are optimization problems with a huge number of possible answers, and optimization is what quantum annealers and algorithms like QAOA are built for. The pitch is easy to understand. The results so far are more modest, and it helps to look at the real ones before spending money on quantum computing in logistics.
What did the public quantum computing pilots in logistics show?
The public quantum computing pilots in logistics showed that hybrid quantum solvers can run on real operational data and, in a few cases, speed up scheduling in production. None of them showed a quantum computer beating the best classical solver, and most compared against older methods or manual processes.
Volkswagen: bus routing in Lisbon (2019)
In November 2019 Volkswagen ran a small fleet of public buses with the operator CARRIS between Lisbon’s airport and the Web Summit venue. A D-Wave quantum computer calculated routes for each bus in near real time to avoid congestion, combined with a passenger demand prediction. It was a genuine live deployment, and a small one. It showed that the pieces could run together, not that quantum routing beat classical routing.
Port of Los Angeles: container handling at Pier 300
SavantX and Fenix Marine Services used an optimization system that ran on D-Wave hardware to schedule trucks and rubber-tired gantry cranes at Pier 300. The published results report more crane deliveries per day and shorter truck waiting times. What the reports do not separate clearly is how much came from the quantum part and how much from rethinking the scheduling process and building a digital twin.
Ford Otosan: production sequencing (2025)
In 2025 Ford Otosan, the Ford and Koç Holding joint venture in Turkey, said it had put a hybrid quantum application built with D-Wave into production to sequence Ford Transit vehicles through a body shop, with a large cut in scheduling time. The Transit comes in a very large number of variants, which is why sequencing is hard. This is manufacturing more than logistics, but the math is the same as dock or crew scheduling.
ExxonMobil and IBM: maritime inventory routing
IBM Research and ExxonMobil studied how to formulate the routing of LNG ships between ports so that quantum algorithms could solve it. The experiments ran on simulated quantum devices. The value was in learning which formulations suit quantum hardware at all.
Quantum-South and IAG Cargo: air cargo loading (2022)
Latin America has its own example. Quantum-South, a startup from Uruguay, ran a proof of concept with IAG Cargo from May 2022 to optimize how unit load devices are loaded onto flights, combining D-Wave’s quantum annealing with classical systems through Amazon Braket. According to The Quantum Insider’s report, the results were promising but preliminary, and IAG Cargo spoke of further phases to confirm them.
Why do quantum pilot results in logistics look better than they are?
Quantum pilot results in logistics often look better than they are because the baseline is weak. Many pilots compare a hybrid quantum solver with a manual process or an old heuristic, not with a modern classical solver, and hybrid solvers do much of their work on classical hardware anyway.
Vehicle routing, scheduling and bin packing have decades of classical research behind them, and commercial solvers handle very large instances well. The hybrid quantum solvers used in the pilots above run a large share of their work on classical hardware. When a pilot reports a big improvement, the first question should be: improvement against what? Often the baseline was a manual process or an old heuristic, and a modern classical solver would have captured much of the gain.
That does not make the pilots worthless. Some companies got faster scheduling in production. But a logistics manager deciding where to spend this year’s budget should compare three options side by side:
| Option | What it needs | What it tells you |
|---|---|---|
| Better classical solver | A modern commercial or open-source solver, clean data | How much of the gain was available without quantum hardware |
| Hybrid quantum solver | Cloud access to a hybrid service, a problem formulation it accepts | Whether the quantum part adds anything over the classical baseline |
| Better data | Accurate demand, time windows and constraints | Often the largest gain, and it helps either solver |
When could quantum optimization pay off in logistics?
Quantum optimization could pay off in logistics once error-corrected, gate-based machines can run algorithms with proven advantages on some problem classes, and no one can yet name the year or the problems. For planning, treat 2026 to 2030 as a period for learning and small, measured experiments.
Gate-based quantum computers with error correction could eventually run optimization algorithms with provable advantages on some problem classes. Nobody can yet say which logistics problems will benefit, or when. For planning purposes, treat 2026 to 2030 as a period for learning and small experiments, and revisit each year based on published results rather than vendor roadmaps.
Which logistics systems need post-quantum cryptography first?
The logistics systems that need post-quantum cryptography first are those that stay in the field for years or carry long-lived signatures: telematics units, trackers, port equipment, customs declarations, electronic bills of lading and partner APIs. They use RSA or elliptic-curve keys, and devices bought now may outlive those algorithms.
GPS trackers, cold-chain sensors and handheld scanners belong on the same list. A large quantum computer would break the keys they rely on, and the UK’s National Cyber Security Centre, in its March 2025 migration timelines, says industrial IoT devices “require special attention in migration planning” because many are resource-constrained or can’t be upgraded.
NIST published the post-quantum standards (FIPS 203, 204 and 205) in August 2024, and its draft transition plan, NIST IR 8547, proposes disallowing RSA and elliptic-curve cryptography at common strengths by 2035. Devices bought in 2026 with no upgrade path could still be in service then. That makes procurement the cheapest place to act: require crypto agility in every new tracking or telematics contract.
What a logistics company should do this year
Choose one optimization problem that costs you real money, such as last-mile routing, yard scheduling or crew rostering. Measure how your current method performs. Then decide whether a better classical solver, a hybrid quantum test or both deserve a small budget. Quantum use case discovery is designed for that screening, and a hybrid quantum proof of concept runs the test with a fair baseline.
At the same time, list the connected devices and signature systems you depend on and ask vendors how they will move to post-quantum algorithms. A quantum readiness assessment covers both sides in a few weeks. We are opening engagements in stages; contact us to join the early-access list.
Sources
- The Quantum Insider, Quantum-South explores quantum algorithms for air cargo optimization, December 2, 2022
- UK NCSC, Timelines for migration to post-quantum cryptography, March 20, 2025
- NIST CSRC, Post-quantum cryptography FIPS approved (FIPS 203, 204 and 205), August 13, 2024
- NIST IR 8547 (initial public draft), Transition to Post-Quantum Cryptography Standards, November 2024