Heterogeneous Differential Evolution for Numerical Optimization

نویسندگان

  • Hui Wang
  • Wenjun Wang
  • Zhihua Cui
  • Hui Sun
  • Shahryar Rahnamayan
چکیده

Differential evolution (DE) is a population-based stochastic search algorithm which has shown a good performance in solving many benchmarks and real-world optimization problems. Individuals in the standard DE, and most of its modifications, exhibit the same search characteristics because of the use of the same DE scheme. This paper proposes a simple and effective heterogeneous DE (HDE) to balance exploration and exploitation. In HDE, individuals are allowed to follow different search behaviors randomly selected from a DE scheme pool. Experiments are conducted on a comprehensive set of benchmark functions, including classical problems and shifted large-scale problems. The results show that heterogeneous DE achieves promising performance on a majority of the test problems.

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عنوان ژورنال:

دوره 2014  شماره 

صفحات  -

تاریخ انتشار 2014