Modeling routing problems in QUBO with application to ride-hailing

Autor: Michele Cattelan, Sheir Yarkoni

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)

Abstract Many emerging commercial services are based on the sharing or pooling of resources for common use with the aim of reducing costs. Businesses such as delivery-, mobility-, or transport-as-a-service have become standard in many parts of the wo

Externí odkaz: https://doaj.org/article/d79accfe517f46638da3dc28675544a6

Quantum annealing for industry applications

Autor: Sheir Yarkoni, Elena Raponi, Thomas Bäck, Sebastian Schmitt

Publikováno v: Reports on Progress in Physics, 85(10):104001

Quantum annealing is a heuristic quantum optimization algorithm that can be used to solve combinatorial optimization problems. In recent years, advances in quantum technologies have enabled the development of small- and intermediate-scale quantum pro

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f48096f51441bcd7ebabb375e02f43a0
https://doi.org/10.1088/1361-6633/ac8c54

Beating classical heuristics for the binary paint shop problem with the quantum approximate optimization algorithm

Autor: Michael Streif, Andrea Skolik, Martin Leib, Florian Neukart, Sheir Yarkoni

Publikováno v: Physical Review A. 104

The binary paint shop problem (BPSP) is an APX-hard optimization problem of the automotive industry. In this work, we show how to use the Quantum Approximate Optimization Algorithm (QAOA) to find solutions of the BPSP and demonstrate that QAOA with c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::123497ca66c361fc8aa9df5efc72f2a8
https://doi.org/10.1103/physreva.104.012403

Semi-supervised time series classification method for quantum computing

Autor: Andrii Kleshchonok, Sheir Yarkoni, Florian Neukart, Marc Hilbert, Yury Dzerin

Publikováno v: Quantum Machine Intelligence. 3

In this paper we develop methods to solve two problems related to time series (TS) analysis using quantum computing: reconstruction and classification. We formulate the task of reconstructing a given TS from a training set of data as an unconstrained

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44d25be552dd69d2d665e0ce61fe3aa3
https://doi.org/10.1007/s42484-021-00042-0

Multi-car paint shop optimization with quantum annealing

Autor: Florian Neukart, David Von Dollen, Thomas Bäck, Sheir Yarkoni, Michael Streif, Alex Alekseyenko

Publikováno v: 2021 IEEE International Conference on Quantum Computing and Engineering (QCE), 35-41. IEEE
STARTPAGE=35;ENDPAGE=41;TITLE=2021 IEEE International Conference on Quantum Computing and Engineering (QCE)
QCE

We present a generalization of the binary paint shop problem (BPSP) to tackle an automotive industry application, the multi-car paint shop (MCPS) problem. The objective of the optimization is to minimize the number of color switches between cars in a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4333be55dbfbddec127e6dd3a73de592
http://hdl.handle.net/1887/3280039