Differential Annealing for Global Optimization

  • Yongwei Zhang
  • Lei Wang
  • Qidi Wu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7331)


This paper propose a hybrid stochastic approach called differential annealing algorithm. The algorithm integrated the advantages of differential evolution and simulated annealing. It can be considered as a swarm-based simulated annealing with differential operator or differential evolution with the Boltzmann-type selection operator. The proposed algorithm is tested on benchmark functions, along with simulated annealing and differential evolution. Results show that differential annealing outperforms the comparative group under the same amount of function evaluations.


Swarm Intelligence Differential Evolution Simulated Annealing Stochastic Search Selection Operator Global Optimization 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yongwei Zhang
    • 1
  • Lei Wang
    • 1
  • Qidi Wu
    • 1
  1. 1.College of Electronics and Information EngineeringTongji UniversityShanghaiP.R. China

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