Optimising Rolling Stock Planning including Maintenance with Constraint Programming and Quantum Annealing

We benchmark the quantum processing units of the largest quantum annealers to date, the $$5000+$$ 5000 + qubit quantum annealer Advantage and its 2000+ qubit predecessor D-Wave 2000Q, using tail assignment and exact cover problems from aircraft scheduling scenarios. The benchmark set contains small, intermediate, and large problems with both sparsely connected and almost fully connected instances. We find that Advantage outperforms D-Wave 2000Q for almost all problems, with a notable increase in success rate and problem size. In particular, Advantage is also able to solve the largest problems with 120 logical qubits that D-Wave 2000Q cannot solve anymore. Furthermore, problems that can still be solved by D-Wave 2000Q are solved faster by Advantage. We find, however, that D-Wave 2000Q can achieve better success rates for sparsely connected problems that do not require the many new couplers present on Advantage, so improving the connectivity of a quantum annealer does not per se improve its performance.

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“…(3) Benchmarks of hybrid solvers that use a combination of QPUs and CPUs or GPUs to solve large-scale application problems [12,18,42,43].…”

Section: Introductionmentioning

confidence: 99%

Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems

Willsch

Calaza

et al. 2022

Quantum Inf Process

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“…To make a stronger statement, the limitations of our model have to be studied further, both analytically (by elaborating e.g., on the more precise determination of α) and empirically by applying the method to many samples. We plan to use it for additional problems of the field of logistics and operations research, similarly to those e.g., in [31,32].…”

Section: Discussionmentioning

confidence: 99%

Statistical quality assessment of Ising-based annealer outputs

Domino,

Koniorczyk,

Puchała

2021

Preprint

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The ability to evaluate the outcomes of quantum annealers is essential for such devices to be used in complex computational tasks. We introduce a statistical test of the quality of Ising-based annealers' output based on the data only, assessing the ground state's probability of being sampled. A higher probability value implies that at least the lower part of the spectrum is a part of the sample. Assuming a plausible model of the univariate energy distribution of the sample, we express the ground-state energy and temperature as a function of cumulants up to the third order. Using the annealer samples, we evaluate this multiple times using Bootstrap resampling, resulting in an estimated histogram of ground-state energies, and deduce the desired parameter on this basis. The approach provides an easily implementable method for the primary validation of Ising-based annealers' output. We demonstrate its behavior through experiments made with actual samples originating from quantum annealer devices.

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“…As for the railway industry, to the best of our knowledge, a preliminary version of the present work [15] was the first to apply a quantum computing approach to a problem in railway optimization. As the citations to our e-print illustrate [16,17], this research direction is attracting increasing interest.…”

Section: Introductionmentioning

confidence: 99%

Quantum Annealing in the NISQ Era: Railway Conflict Management

Domino

Koniorczyk

Krawiec

et al. 2023

Entropy

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We are in the noisy intermediate-scale quantum (NISQ) devices’ era, in which quantum hardware has become available for application in real-world problems. However, demonstrations of the usefulness of such NISQ devices are still rare. In this work, we consider a practical railway dispatching problem: delay and conflict management on single-track railway lines. We examine the train dispatching consequences of the arrival of an already delayed train to a given network segment. This problem is computationally hard and needs to be solved almost in real time. We introduce a quadratic unconstrained binary optimization (QUBO) model of this problem, which is compatible with the emerging quantum annealing technology. The model’s instances can be executed on present-day quantum annealers. As a proof-of-concept, we solve selected real-life problems from the Polish railway network using D-Wave quantum annealers. As a reference, we also provide solutions calculated with classical methods, including the conventional solution of a linear integer version of the model as well as the solution of the QUBO model using a tensor network-based algorithm. Our preliminary results illustrate the degree of difficulty of real-life railway instances for the current quantum annealing technology. Moreover, our analysis shows that the new generation of quantum annealers (the advantage system) does not perform well on those instances, either.

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Optimising Rolling Stock Planning including Maintenance with Constraint Programming and Quantum Annealing

Cited by 4 publications

References 17 publications

Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems

Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems

Statistical quality assessment of Ising-based annealer outputs

Quantum Annealing in the NISQ Era: Railway Conflict Management

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