AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
A Pipeline-Based Genetic Algorithm Accelerator for Time-Critical Processes in Real-Time Systems
IEEE Transactions on Computers
Expert Systems with Applications: An International Journal
Investigating generalization in parallel evolutionary artificial neural networks
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Parallel implementation of evolutionary strategies on heterogeneous clusters with load balancing
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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Abstract: Genetic algorithms have been used successfully as a global optimization method when the search space is very large. To characterize and analyze the performance of genetic algorithms on a cluster of workstations, a parallel version of the GENESIS 5.0 was developed using PVM 3.3. This version, called VMGENESIS, was used to study a nonlinear least-squares problem. Performance results show that linear speedups can be achieved if the basic distributed genetic algorithm is combined with a simple dynamic load-balancing mechanism. Results also show that the quality of search changes significantly with the number of processors involved in the computation and with the frequency of communication.