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

  • Daniel Leal Souza
  • Otávio Noura Teixeira
  • Dionne Cavalcante Monteiro
  • Roberto Célio Limão de Oliveira
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 23)


This paper presents a new Cooperative Evolutionary Multi-Swarm Optimization Algorithm (CEMSO-GPU) based on CUDA parallel architecture applied to solve engineering problems. The focus of this approach is: the use of the concept of master/slave swarm with a mechanism of data sharing; and, the parallelism method based on the paradigm of General Purpose Computing on Graphics Processing Units (GPGPU) with CUDA architecture, brought by NVIDIA corporation. 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 (WBD, ATD, MWTCS, SRD-11) and the results compared to other approaches.


PSO EPSO GPGPU GPU CUDA NVIDIA  Swarm Cooperative Parallel Hetergeneus computing  Particle 



This work is supported financially by Research Support Foundation of Par(FAPESPA) and Federal University of Pará (UFPA).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Daniel Leal Souza
    • 2
    • 1
  • Otávio Noura Teixeira
    • 1
    • 3
  • Dionne Cavalcante Monteiro
    • 2
  • Roberto Célio Limão de Oliveira
    • 3
  1. 1.Laboratory of Natural Computing (LCN) Area of Exact and Natural Sciences (ACET)University Centre of Pará (CESUPA)BelémBrazil
  2. 2.Institute of Exact and Natural Sciences (ICEN), Laboratory of Applied Artificial Intelligence (LAAI)Federal University of Pará (UFPA)BelémBrazil
  3. 3.Institute of Technology (ITEC), Post-Graduate Program in Electrical Engineering (PPGEE)Federal University of Para (UFPA)BelémBrazil

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