Implementation of a Hybrid Classical-Quantum Annealing Algorithm for Logistic Network Design

The logistic network design is an abstract optimization problem that, under the assumption of minimal cost, seeks optimal configuration supply chain’s infrastructures and facilities based on customer demand. Key economic decisions are taken about location, number, size manufacturing warehouses solution. Therefore, improvements in methods to address this question, which known be NP-hard complexity class, would have relevant financial consequences. Here, we implement D-Wave quantum annealer a hybrid classical-quantum annealing algorithm. cost function with constraints translated spin Hamiltonian, whose ground state encodes searched result. As benchmark, measure accuracy results for set paradigmatic problems against published solutions (the error average below $$1\%$$ ), performance compared classical algorithm, showing remarkable reduction number iterations. This work shows that state-of-the-art annealers may codify solve supply-chain even still far from useful supremacy.