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

التفاصيل البيبلوغرافية
العنوان: Optimising Rolling Stock Planning including Maintenance with Constraint Programming and Quantum Annealing
المؤلفون: Bickert, Patricia, Grozea, Cristian, Hans, Ronny, Koch, Matthias, Riehn, Christina, Wolf, Armin
سنة النشر: 2021
المجموعة: Computer Science
Quantitative Finance
مصطلحات موضوعية: Computer Science - Artificial Intelligence, Quantitative Finance - Statistical Finance
الوصف: 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.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2109.07212
رقم الأكسشن: edsarx.2109.07212
قاعدة البيانات: arXiv