Binary Differential Evolution algorithm with new mutation operator

Author(s):  
Changshou Deng ◽  
Changyong Liang ◽  
Yanling Yang ◽  
Bingyan Zhao ◽  
Hai Zhang
Author(s):  
Morteza Alinia Ahandani ◽  
Seyyed Sadegh Bibak Sareshkeh

The shuffled differential evolution (SDE) is a recently proposed version of differential evolution (DE). However the SDE employs several efforts to compensate limited amount of search moves in the original DE, but these efforts are performed by the same operator. To vary search moves of the SDE, this research proposes employing a secondary mutation operator beside of first mutation operator. This new mutation operator can generate some different offspring than those generated by the first one. Experiments demonstrate a better performance of the proposed algorithm than the SDE. In a later part of the comparative experiments, performance comparisons of the proposed algorithm with some modern DE and other evolutionary algorithms reported in the literature confirm a better or at least a competitive performance of our proposed algorithm. Also a real-world optimization problem, namely, Spread Spectrum Radar Polly phase Code Design, is solved to show the wide applicability of the DSDE.


2020 ◽  
Vol 24 (18) ◽  
pp. 14221-14234
Author(s):  
Amir Karbassi Yazdi ◽  
Mohamad Amin Kaviani ◽  
Thomas Hanne ◽  
Andres Ramos

2015 ◽  
Vol 31 (4) ◽  
pp. 361-380 ◽  
Author(s):  
Alfonso Martinez Cruz ◽  
Ricardo Barrón Fernández ◽  
Herón Molina Lozano ◽  
Marco Antonio Ramírez Salinas ◽  
Luis Alfonso Villa Vargas

2019 ◽  
Vol 10 (1) ◽  
pp. 1-28 ◽  
Author(s):  
Ali Wagdy Mohamed ◽  
Ali Khater Mohamed ◽  
Ehab Z. Elfeky ◽  
Mohamed Saleh

The performance of Differential Evolution is significantly affected by the mutation scheme, which attracts many researchers to develop and enhance the mutation scheme in DE. In this article, the authors introduce an enhanced DE algorithm (EDDE) that utilizes the information given by good individuals and bad individuals in the population. The new mutation scheme maintains effectively the exploration/exploitation balance. Numerical experiments are conducted on 24 test problems presented in CEC'2006, and five constrained engineering problems from the literature for verifying and analyzing the performance of EDDE. The presented algorithm showed competitiveness in some cases and superiority in other cases in terms of robustness, efficiency and quality the of the results.


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