2022 ◽  
Vol 13 (1) ◽  
pp. 0-0

Differential evolution (DE), an important evolutionary technique, enhances its parameters such as, initialization of population, mutation, crossover etc. to resolve realistic optimization issues. This work represents a modified differential evolution algorithm by using the idea of exponential scale factor and logistic map in order to address the slow convergence rate, and to keep a very good equilibrium linking exploration and exploitation. Modification is done in two ways: (i) Initialization of population and (ii) Scaling factor.The proposed algorithm is validated with the aid of a 13 different benchmark functions taking from the literature, also the outcomes are compared along with 7 different popular state of art algorithms. Further, performance of the modified algorithm is simulated on 3 realistic engineering problems. Also compared with 8 recent optimizer techniques. Again from number of function evaluations it is clear that the proposed algorithm converses more quickly than the other existing algorithms.


2014 ◽  
Vol 931-932 ◽  
pp. 1129-1133
Author(s):  
Natee Panagant ◽  
Sujin Bureerat

A differential evolution (DE) algorithm has been employed to approximate the solution of a nonlinear single pendulum equation. The solution has been approximated as a Fourier series expansion form. Then, weighted-residual and penalty functions are employed to transform the problem into a constrained optimization problem while optimum solutions will be carried out by DE. This paper also studies an effect of a scaling factor of DE to the results. The results reveal that the scaling factor significantly affects the convergent speed and accuracy of DE. Approximate solutions well agree with the exact solutions for the scaling factor being 0.5.


2022 ◽  
Vol 13 (1) ◽  
pp. 1-15
Author(s):  
Katyayani Kashyap ◽  
Sunil Pathak ◽  
Narendra Singh Yadav

Differential evolution (DE), an important evolutionary technique, enhances its parameters such as, initialization of population, mutation, crossover etc. to resolve realistic optimization issues. This work represents a modified differential evolution algorithm by using the idea of exponential scale factor and logistic map in order to address the slow convergence rate, and to keep a very good equilibrium linking exploration and exploitation. Modification is done in two ways: (i) Initialization of population and (ii) Scaling factor.The proposed algorithm is validated with the aid of a 13 different benchmark functions taking from the literature, also the outcomes are compared along with 7 different popular state of art algorithms. Further, performance of the modified algorithm is simulated on 3 realistic engineering problems. Also compared with 8 recent optimizer techniques. Again from number of function evaluations it is clear that the proposed algorithm converses more quickly than the other existing algorithms.


2009 ◽  
Vol 29 (4) ◽  
pp. 1046-1047
Author(s):  
Song-shun ZHANG ◽  
Chao-feng LI ◽  
Xiao-jun WU ◽  
Cui-fang GAO

2013 ◽  
Vol 8 (999) ◽  
pp. 1-6
Author(s):  
Chuii Khim Chong ◽  
Mohd Saberi Mohamad ◽  
Safaai Deris ◽  
Mohd Shahir Shamsir ◽  
Lian En Chai ◽  
...  

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