YesBit
A bit is a switch: it is either 0 or 1. Every classical route planner is built from switches, so it can only ever examine one candidate route at a time, one after another.
QUANTUM EXPLAINED
Qubits, superposition, and better routes.
No physics degree required. This page explains what a qubit actually is, why superposition searches a space classical algorithms have to walk step by step, and how YesAndNo turns that into a route a dispatcher can use today.
Qubit
A qubit is not a switch but a direction — it can point anywhere between 0 and 1. Only when you measure it does it settle on one answer.
Superposition
Before measurement a qubit holds both possibilities together. Ten qubits hold 1,024 combinations at the same time; fifty hold more combinations than a classical machine could list in a lifetime.
Entanglement
Linked qubits behave as one system: fix one and the others respond. That is exactly what an operational constraint is — 'if this van takes the morning slot, that technician cannot'.
Interference
Bad combinations are made to cancel each other out while good ones reinforce. The measurement is then overwhelmingly likely to land on a strong solution rather than a random one.
Measurement
Reading the system collapses the superposition into a single concrete assignment — one route, one schedule, one dock sequence you can hand to an operator.
WHY IT BEATS CLASSICAL ROUTING
A classical solver walks the maze. Quantum floods it.
Add one more stop to a route and the number of possible orderings multiplies. At real operational size the list of candidates is larger than any machine can enumerate, so classical algorithms take shortcuts: they sample, they follow rules of thumb, and they stop at the first decent answer they find. That answer is usually tens of percent away from the best one — and nobody ever sees the gap, because the better route was never examined.
A quantum pass does not enumerate. It holds the whole viable frontier at once and lets the physics push probability towards the strong solutions. That is why the improvement shows up on exactly the problems classical planning calls “good enough”.
The problem is described, not coded
Vehicles, technicians, aisles, time windows, capacities, costs and priorities enter the metadata layer as constraints. Nothing is hard-wired to an industry.
The impossible is pruned classically
Combinations that violate a hard constraint are removed before any quantum work begins. This is cheap, and it shrinks the search to its irreducible core.
The core is encoded into qubits
Each remaining decision becomes a qubit; each constraint becomes a link between qubits. The whole viable frontier now exists at once, in superposition.
Interference favours the good routes
Cost, time and ROI targets shape the system so that expensive combinations cancel and efficient ones amplify.
One measured answer, benchmarked
The system is measured, and the result is scored against the classical baseline it replaces — so the improvement is a number, not a claim.