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IMPLEMENTED_NOT_INDEPENDENTLY_VERIFIEDTruck + drone

ALGORITHM ARTICLE

QUBO + classical annealing

Problem. Heuristic fixed-tour sortie selection in QUBO form.

Core idea. Reward savings and penalize simultaneous conflicting sorties.

Procedure

  1. Build linear rewards and quadratic penalties.
  2. Run seeded classical annealing.
  3. Decode and verify feasibility.

Certificate. Energy and feasibility only; no exact certificate.

Data structures and API

from optfin_orlab import TruckDroneProblem

solver = TruckDroneProblem()
result = solver.solve_qubo_annealing(...)

Complexity. Restarts × sweeps × candidate interactions

Limits. Classical baseline; zero claim of quantum advantage.

OPTFIN AUDIT CHECKS

What has to reconcile before this method is trusted.

  • DefinitionProblem, objective, inputs and output are explicit.
  • Data structureThe public API and canonical source path are identified.
  • CorrectnessEnergy and feasibility only; no exact certificate.
  • ComplexityRestarts × sweeps × candidate interactions
  • Operational limitClassical baseline; zero claim of quantum advantage.
  • ReproductionSource, executable test and evidence route remain linked.
View sourceOpen executable testReproduce evidence

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