Name
Abstract | ||
|---|---|---|
A parallel simulated annealing method, IIP, is applied to the n-queen problem. By this method, identical multiple copies of the single process algorithm are independently run in parallel. This technique gives superlinear speedup, in some cases on the order of 50 using only 8 processors. Convergence to the solution exceeds 99.96% for as few as 4 processors. In addition, simulated annealing was compared with a constant temperature version of itself since the resulting homogeneous Markov chain is amendable to Perron-Frobenius analysis. The two algorithms perform similarly. |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1109/IPPS.1993.262797 | Newport, CA |
Keywords | Field | DocType |
sampling methods,parallel algorithms,markov chain,temperature,thermodynamics,energy states,mathematics,stochastic processes,simulated annealing | Convergence (routing),Simulated annealing,Mathematical optimization,Energy level,Parallel algorithm,Markov chain,Stochastic process,Algorithm,Adaptive simulated annealing,Mathematics,Speedup | Conference |
ISBN | Citations | PageRank |
0-8186-3442-1 | 0 | 0.34 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ron Shonkwiler | 1 | 75 | 9.67 |
| Farzad Ghannadian | 2 | 7 | 1.56 |
| Cecil O. Alford | 3 | 27 | 7.87 |