Workshop Description
Full-day workshop on quantum optimisation for logistics operations. Covers vehicle routing as QUBO, warehouse pick-path optimisation via quantum annealing, last-mile delivery rerouting, and workforce scheduling with honest NISQ hardware benchmarks.
Logistics operations are built on combinatorial optimisation problems. Vehicle routing with capacity constraints and time windows, warehouse pick-path sequencing, container loading, workforce shift assignment: these are NP-hard or NP-complete problems where solution quality directly affects cost. Quantum computing offers a different computational approach to these problems through QUBO (Quadratic Unconstrained Binary Optimisation) formulations. This workshop teaches participants to formulate specific logistics problems as QUBOs, solve them using both quantum annealing (D-Wave Advantage, 5000+ qubits) and gate-based QAOA (Farhi et al. 2014), and benchmark results against established classical solvers like Google OR-Tools and Gurobi. Current quantum hardware handles roughly 150-200 fully connected variables after minor embedding, which limits practical problem sizes. The workshop is direct about these constraints while also covering quantum-inspired classical solvers (Fujitsu Digital Annealer, Toshiba SQBM+) that handle 100,000+ variables on existing infrastructure and may be the right near-term choice for many logistics organisations.
What participants cover
- QUBO formulation for logistics: translating vehicle routing, bin packing, and scheduling problems into quantum-compatible representations
- Quantum annealing for logistics: D-Wave Advantage architecture, minor embedding, chain strength calibration, and hybrid solver integration
- QAOA for combinatorial decisions: MaxCut reduction, variational parameter optimisation, and circuit depth requirements on gate-based hardware
- Last-mile and warehouse operations: dynamic rerouting, pick-path optimisation, and container loading as constrained optimisation problems
- Classical benchmarking: comparing quantum solutions against Google OR-Tools, Gurobi, and simulated annealing on matched problem instances
- Quantum-inspired alternatives: Fujitsu Digital Annealer and Toshiba SQBM+ for logistics-scale problems deployable on current infrastructure