A Comparative Study of Three GPU-Based Metaheuristics

  • Youssef S. G. Nashed
  • Pablo Mesejo
  • Roberto Ugolotti
  • Jérémie Dubois-Lacoste
  • Stefano Cagnoni
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7492)


In this paper we compare GPU-based implementations of three metaheuristics: Particle Swarm Optimization, Differential Evolution, and Scatter Search. A GPU-based implementation, obviously, does not change the general properties of the algorithms. As well, we give for granted that GPU-based implementation of both algorithm and fitness function produces a significant speed-up with respect to a sequential implementation. Accordingly, the main goal of this work has been to fairly assess the efficiency of the GPU-based implementations of the three metaheuristics, based on the statistical analysis of the results they obtain in optimizing a benchmark of twenty functions within a prefixed limited time.


Global Continuous Optimization Particle Swarm Optimization Differential Evolution Scatter Search GPGPU 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Youssef S. G. Nashed
    • 1
  • Pablo Mesejo
    • 1
  • Roberto Ugolotti
    • 1
  • Jérémie Dubois-Lacoste
    • 2
  • Stefano Cagnoni
    • 1
  1. 1.Department of Information EngineeringUniversity of ParmaItaly
  2. 2.IRIDIA, CoDEUniversité Libre de BruxellesBelgium

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