A parallelized sequential random search global optimization algorithm
This work deals with a stochastic global optimization algorithm, called CRS (Controlled Random Search), which originally was devised as a sequential algorithm. Our work is intended to analyze the degree of parallelism that can be introduced into CRS and to propose a new refined parallel CRS algorith...
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| Format: | Article |
| Published: |
1999
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| Series: | Acta cybernetica
14 No. 2 |
| Kulcsszavak: | Számítástechnika, Kibernetika, Algoritmus |
| Subjects: | |
| Online Access: | http://acta.bibl.u-szeged.hu/12635 |
| Summary: | This work deals with a stochastic global optimization algorithm, called CRS (Controlled Random Search), which originally was devised as a sequential algorithm. Our work is intended to analyze the degree of parallelism that can be introduced into CRS and to propose a new refined parallel CRS algorithm (RPCRS). As a first stage, evaluations of RPCR S were carried out by simulating parallel implementations. The degree of parallelism of RPCR S is controlled by a user given parameter whose value must be tuned to the size of the parallel computer system. It will be shown that the greater the degree of parallelism is the better the performance of the sequential and parallel executions are. |
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| Physical Description: | 403-418 |
| ISSN: | 0324-721X |