QUasi-Affine TRansformation Evolution with External ARchive (QUATRE-EAR): An enhanced structure for Differential Evolution

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摘要

Optimization demands are ubiquitous in science and engineering. The key point is that the approach to tackle a complex optimization problem should not itself be difficult. Differential Evolution (DE) is such a simple method, and it is arguably a very powerful stochastic real-parameter algorithm for single-objective optimization. However, the performance of DE is highly dependent on control parameters and mutation strategies. Both tuning the control parameters and selecting the proper mutation strategy are still tedious but important tasks for users. In this paper, we proposed an enhanced structure for DE algorithm with less control parameters to be tuned. The crossover rate control parameter Cr is replaced by an automatically generated evolution matrix and the control parameter F can be renewed in an adaptive manner during the whole evolution. Moreover, an enhanced mutation strategy with time stamp mechanism is advanced as well in this paper. CEC2013 test suite for real-parameter single objective optimization is employed in the verification of the proposed algorithm. Experiment results show that our proposed algorithm is competitive with several well-known DE variants.

论文关键词:Benchmark functions,Differential evolution,QUATRE-EAR algorithm,Real-parameter optimization,Single-objective optimization

论文评审过程:Received 24 August 2017, Revised 6 March 2018, Accepted 27 April 2018, Available online 27 April 2018, Version of Record 28 May 2018.

论文官网地址:https://doi.org/10.1016/j.knosys.2018.04.034