Name
Abstract | ||
|---|---|---|
The authors present a problem-independent general-purpose parallel implementation of simulated annealing (SA) on distributed message-passing multiprocessor systems. The sequential algorithm is studied, and a classification of combinatorial optimization problems together with their neighborhood structures is given. Several parallelization approaches are examined, considering their suitability for problems of the various classes. For typical representatives of the different classes, good parallel SA implementations are presented. A novel parallel SA algorithm that works simultaneously on several Markov chains and decreases the number of chains dynamically is presented. This method yields good results with a parallel self-adapting cooling schedule. All algorithms are implemented in OCCAM-2 on a free configurable transputer system. Measurements on various numbers of processors up to 128 transputers are presented. |
Year | DOI | Venue |
|---|---|---|
1992 | 10.1109/SPDP.1992.242758 | Arlington, TX |
Keywords | Field | DocType |
computer simulation,simulated annealing,mathematics,combinatorial optimization,very large scale integration,markov processes,markov chains,message passing,computational modeling,computer science,distributed processing,parallel algorithms,classification | Simulated annealing,Markov process,Computer science,Parallel algorithm,Transputer,Parallel computing,Markov chain,Combinatorial optimization,Multiprocessing,Sequential algorithm,Distributed computing | Conference |
ISBN | Citations | PageRank |
0-8186-3200-3 | 5 | 0.65 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ralf Diekmann | 1 | 281 | 28.99 |
| Reinhard Lüling | 2 | 313 | 35.55 |
| Jens Simon | 3 | 5 | 0.65 |