Title :
Effect of pseudo gradient on differential evolutionary for global numerical optimization
Author :
Jinliang Ding ; Lipeng Chen ; Qingguang Xie ; Tianyou Chai ; Xiuping Zheng
Author_Institution :
State Key Lab. of Synthetical Autom. for Process Ind., Northeastern Univ., Shenyang, China
Abstract :
In this paper, a novel pseudo gradient based DE approach is proposed, which takes advantage of both the differential evolutionary (DE) and the gradient-based algorithm. The gradient information, which is called pseudo gradient, is generated through randomly selected two vectors and their fitness function values. This work is to investigate the effect of proposed pseudo gradient on differential evolutionary algorithm. The simulation results show that DE with pseudo gradient can obtain better performance overall in comparison with classical DE variants. The pseudo gradient based DE with adaptive parameter section is compared with the existing adaptive DE algorithms. Also, the control parameter, step size are investigated to understand the mechanism of pseudo gradient in detail.
Keywords :
evolutionary computation; gradient methods; adaptive DE algorithm; adaptive parameter section; control parameter; differential evolutionary algorithm; fitness function values; global numerical optimization; gradient information; gradient-based algorithm; pseudogradient based DE approach; randomly selected vectors; step size; Convergence; Evolutionary computation; Optimization; Radio frequency; Sociology; Statistics; Vectors;
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
DOI :
10.1109/CEC.2014.6900463
