Abstract
We introduce a parallel scheme for simulated annealing, a widely used Markov chain Monte Carlo (MCMC) method for optimization. Our method is constructed and analyzed under the classical framework of MCMC. The benchmark function for optimization is used for validation and verification of the parallel scheme. The experimental results, along with the proof based on statistical theory, provide us with insights into the mechanics of the parallelization of simulated annealing for high parallel efficiency or scalability for large parallel computers.
Original language | English (US) |
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Pages (from-to) | 227-237 |
Number of pages | 11 |
Journal | Monte Carlo Methods and Applications |
Volume | 25 |
Issue number | 3 |
DOIs | |
State | Published - Sep 1 2019 |
Keywords
- global optimization
- Markov chain Monte Carlo
- Parallel computing
- simulated annealing
ASJC Scopus subject areas
- Statistics and Probability
- Applied Mathematics