Name
Abstract | ||
|---|---|---|
Annealing computation has recently attracted attention as it can efficiently solve various combinatorial optimization problems using an Ising model. Stochastic cellular automata annealing (SCA) is a promising algorithm that can realize fast spin-update by utilizing its parallel computing capability. However, in SCA, preparing an appropriate control of the pinning parameter is a hard task, which degrades its usability. This paper proposes a novel approach called APC-SCA (Autonomous Pinning effect Control SCA) where the spin pinning parameter can be controlled autonomously by observing individual spin flips. The evaluation results using max-cut and N-queen problems demonstrate that the proposed approach can obtain better solutions than the conventional approach with a grid search of optimal pinning parameter control. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/IPDPSW55747.2022.00078 | 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) |
Keywords | DocType | ISSN |
combinatorial optimization,cellular automata,stochastic algorithm,parallel annealing,Ising model | Conference | 2164-7062 |
ISBN | Citations | PageRank |
978-1-6654-9748-0 | 0 | 0.34 |
References | Authors | |
2 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daiki Okonogi | 1 | 0 | 0.34 |
| Satoru Jimbo | 2 | 0 | 0.34 |
| Kota Ando | 3 | 0 | 0.34 |
| Thiem Van Chu | 4 | 1 | 2.74 |
| Jaehoon Yu | 5 | 0 | 0.34 |
| Masato Motomura | 6 | 0 | 0.34 |
| Kazushi Kawamura | 7 | 0 | 0.34 |