Multiple Exponential Recombination for Differential Evolution

Xin Qiu, Kay Chen Tan, Jian Xin Xu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

68 Citations (Scopus)


Differential evolution (DE) is a popular population-based metaheuristic approach for solving numerical optimization problems. In recent years, considerable research has been devoted to the development of new mutation strategies and parameter adaptation mechanisms. However, as one of the basic algorithmic components of DE, the crossover operation has not been sufficiently examined in existing works. Most of the main DE variants solely employ traditional binomial recombination, which has intrinsic limitations in handling dependent subsets of variables. To fill this research niche, we propose a multiple exponential recombination that inherits all the main advantages of existing crossover operators while possessing a stronger ability in managing dependent variables. Multiple segments of the involved solutions will be exchanged during the proposed operator. The properties of the new scheme are examined both theoretically and empirically. Experimental results demonstrate the robustness of the proposed operator in solving problems with unknown variable interrelations.

Original languageEnglish
Article number7434010
Pages (from-to)995-1006
Number of pages12
JournalIEEE Transactions on Cybernetics
Issue number4
Publication statusPublished - Apr 2017
Externally publishedYes


  • Crossover operator
  • Differential evolution (DE)
  • Variable interrelation

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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