Optimising Rolling Stock Planning including Maintenance with Constraint Programming and Quantum Annealing
arXiv:2109.07212
Abstract
We propose and compare Constraint Programming (CP) and Quantum Annealing (QA) approaches for rolling stock assignment optimisation considering necessary maintenance tasks. In the CP approach, we model the problem with an Alldifferent constraint, extensions of the Element constraint, and logical implications, among others. For the QA approach, we develop a quadratic unconstrained binary optimisation (QUBO) model. For evaluation, we use data sets based on real data from Deutsche Bahn and run the QA approach on real quantum computers from D-Wave. Classical computers are used to evaluate the CP approach as well as tabu search for the QUBO model. At the current development stage of the physical quantum annealers, we find that both approaches tend to produce comparable results.
References in corpus (6)
- Supplementary information for "Quantum supremacy using a programmable superconducting processor"
- A Quantum Approximate Optimization Algorithm
- A Tutorial on Formulating and Using QUBO Models
- Flight Gate Assignment with a Quantum Annealer
- Quantum Shuttle: Traffic Navigation with Quantum Computing
- Quantum computing approach to railway dispatching and conflict management optimization on single-track railway lines