Self-adaptive competitive differential evolution for dynamic environments

2011 ◽  
Author(s):  
Mathys C. du Plessis ◽  
Andries P. Engelbrecht
Keyword(s):  
Differential Evolution ◽  
Dynamic Environments ◽  
Self Adaptive

Self-adaptive, multipopulation differential evolution in dynamic environments

2013 ◽  
Vol 17 (10) ◽  
pp. 1861-1881 ◽  
Author(s):  
Pavel Novoa-Hernández ◽  
Carlos Cruz Corona ◽  
David A. Pelta
Keyword(s):  
Differential Evolution ◽  
Dynamic Environments ◽  
Self Adaptive

scholarly journals Research on the inverse kinematics of manipulator using an improved self-adaptive mutation differential evolution algorithm

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110144
Author(s):  
Qianqian Zhang ◽  
Daqing Wang ◽  
Lifu Gao
Keyword(s):  
Differential Evolution ◽  
Objective Function ◽  
Inverse Kinematics ◽  
Differential Evolution Algorithm ◽  
Weight Coefficient ◽  
Adaptive Mutation ◽  
Feasible Region ◽  
Serial Manipulators ◽  
De Algorithm ◽  
Self Adaptive

To assess the inverse kinematics (IK) of multiple degree-of-freedom (DOF) serial manipulators, this article proposes a method for solving the IK of manipulators using an improved self-adaptive mutation differential evolution (DE) algorithm. First, based on the self-adaptive DE algorithm, a new adaptive mutation operator and adaptive scaling factor are proposed to change the control parameters and differential strategy of the DE algorithm. Then, an error-related weight coefficient of the objective function is proposed to balance the weight of the position error and orientation error in the objective function. Finally, the proposed method is verified by the benchmark function, the 6-DOF and 7-DOF serial manipulator model. Experimental results show that the improvement of the algorithm and improved objective function can significantly improve the accuracy of the IK. For the specified points and random points in the feasible region, the proportion of accuracy meeting the specified requirements is increased by 22.5% and 28.7%, respectively.

A hybrid self-adaptive invasive weed algorithm with differential evolution

2021 ◽  
pp. 1-25
Author(s):  
Fuqing Zhao ◽  
Songlin Du ◽  
Hao Lu ◽  
Weimin Ma ◽  
Houbin Song
Keyword(s):  
Differential Evolution ◽  
Invasive Weed ◽  
Self Adaptive
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