Fast Hybrid BSA-DE-SA Algorithm on GPU

  • Mathieu BrévilliersEmail author
  • Omar Abdelkafi
  • Julien Lepagnot
  • Lhassane Idoumghar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10103)


This paper introduces a hybridization of Backtracking Search Optimization Algorithm (BSA) with Differential Evolution (DE) and Simulated Annealing (SA) in order to improve the convergence speed of BSA. An experimental study, conducted on 20 benchmark problems, shows that this approach outperforms BSA and two other hybridizations [4, 18], in terms of solution quality and convergence speed. We also describe our CUDA implementation of this algorithm for graphics processing unit (GPU). Experimental results are reported for 10 high-dimensional benchmark problems, and it highlights that significant speedup can be achieved.


Continuous optimization Hybrid metaheuristic Backtracking search optimization algorithm Differential evolution Simulated annealing Graphics processing unit CUDA 


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Mathieu Brévilliers
    • 1
    Email author
  • Omar Abdelkafi
    • 1
  • Julien Lepagnot
    • 1
  • Lhassane Idoumghar
    • 1
  1. 1.Université de Haute-Alsace (UHA), LMIA (E.A. 3993)MulhouseFrance

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