Solver engine · Preview · Allocation & Packing
QG-ALLOC.
Where does everything go, and how much? QG-ALLOC places goods, capacity and resources against constrained space and demand — from warehouse layout to facility location to dispatch.
Overview
Allocation & Packing.
Same core, newer engine
QG-ALLOC shares QG-CORE's intake, formulation and backend routing with the more mature engines.
Benchmarked first
We measure against your current allocation approach before you change anything.
Your constraints
Capacity, adjacency, and service-level constraints you already operate under — respected, not simplified away.
Canonical problems
What QG-ALLOC solves.
Industries
Where it applies.
Methods
Quantum-inspired allocation.
QG-ALLOC compiles allocation and packing problems to QUBO/Ising form and solves them with quantum-inspired evolutionary and swarm search, with hybrid decomposition for large-scale multi-echelon problems. It shares QG-CORE's classification and backend-routing layer with every other engine.
Research behind this engine
Multi-processor resource allocation and warehouse layout research at QuMatrix — the foundation QG-ALLOC is being productized from.
Proof of value
No published number yet — and we're saying so.
QG-ALLOC is in preview: the underlying allocation and packing research is mature, but we don't yet have an independently benchmarked figure to publish for it, the way we do for QG-ROUTE and QG-SCHED. The honest version is this — same archetype, same-caliber techniques, and when we run it against your data, that benchmark is the number that counts.
FAQ
Straight answers.
Is this actually quantum?
QG-ALLOC is quantum-inspired and hybrid quantum-classical by design, on the same QG-CORE orchestration as every other engine. As with all our engines, we're transparent about which solver handled which job.
What's the maturity?
Preview. The research and formulation are ready; we're onboarding design partners to run the first benchmarked pilots before we publish a number.
Can I still run a pilot today?
Yes — a benchmark on your data is exactly how a preview engine earns its first published number. Get in touch to scope one.
What data do you need to start?
Historical allocation or packing decisions, the constraints you operate under, and current costs or utilization. Anonymized or sampled data is fine for a first benchmark.
Be one of the first benchmarks for QG-ALLOC.
Thirty minutes to scope a pilot, a clear benchmark on your own data, and an honest read on whether it's worth going further.
Contact us →