TY - GEN
T1 - Practical Effectiveness of Quantum Annealing for Shift Scheduling Problem
AU - Hamada, Natsuki
AU - Saito, Kazuhiro
AU - Kawashima, Hideyuki
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Quantum annealing (QA) is a novel computing approach for solving computationally demanding problems more rapidly than approaches using classical computers by exploiting parallelism in the variable state updates (spin updates). A number of previous studies have shown that QA performs well in benchmarking combinatorial optimization problems, but no works have evaluated QA in the shift scheduling problem. This paper formulates it for QA and evaluates the effectiveness of QA in comparison with other methods on a classical computer. We confirmed that QA is up to about 14 times faster than classical methods in obtaining high-quality solutions for several instances.
AB - Quantum annealing (QA) is a novel computing approach for solving computationally demanding problems more rapidly than approaches using classical computers by exploiting parallelism in the variable state updates (spin updates). A number of previous studies have shown that QA performs well in benchmarking combinatorial optimization problems, but no works have evaluated QA in the shift scheduling problem. This paper formulates it for QA and evaluates the effectiveness of QA in comparison with other methods on a classical computer. We confirmed that QA is up to about 14 times faster than classical methods in obtaining high-quality solutions for several instances.
KW - Combinatorial optimization
KW - Quantum annealing
KW - Shift scheduling
UR - http://www.scopus.com/inward/record.url?scp=85136217376&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85136217376&partnerID=8YFLogxK
U2 - 10.1109/IPDPSW55747.2022.00079
DO - 10.1109/IPDPSW55747.2022.00079
M3 - Conference contribution
AN - SCOPUS:85136217376
T3 - Proceedings - 2022 IEEE 36th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2022
SP - 421
EP - 424
BT - Proceedings - 2022 IEEE 36th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 36th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2022
Y2 - 30 May 2022 through 3 June 2022
ER -