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A New Cooperative Evolutionary Multi-Swarm Optimizer Algorithm Based on CUDA Parallel Architecture Applied to Solve Engineering Optimization Problems

Daniel Leal Souza, Otavio Noura Teixeira, Dionne Cavalcante Monteiro, Roberto Celio Limao de Oliveira
Laboratory of Natural Computing (LCN), Area of Exact and Natural Sciences (ACET), University Centre of Para (CESUPA), Belem, Brazil
3rd International Workshop on Combinations of Intelligent Methods and Applications (CIMA’12), 2012

@inproceedings{souza2012new,

   title={A New Cooperative Evolutionary Multi-Swarm Optimizer Algorithm Based on CUDA Parallel Architecture Applied to Solve Engineering Optimization Problems},

   author={Souza, D.L. and Teixeira, O.N. and Monteiro, D.C. and de Oliveira, R.C.L.},

   booktitle={3rdInternational Workshop on Combinations of Intelligent Methods and Applications (CIMA 2012)},

   pages={49},

   year={2012}

}

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This paper presents a new Cooperative Evolutionary MultiSwarm Optimization Algorithm (CEMSO-GPU) based on CUDA parallel architecture applied to solve engineering problems. The focus on this approach is: The use of the concept of master/slave swarm with a mechanism of sharing data; and, the parallelism method based on the paradigm of General Purpose Computing on Graphics Processing Units (GPGPU) with NVIDIA-CUDA architecture. All these improvements were made aiming to produce better solutions in fewer iterations of the algorithm and to improve the search for best results. The algorithm was tested for some well-known engineering problems (ATD, WBD and SRD-25) and the results compared to other approaches.
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