A particle swarm inspired multi-elitist artificial bee colony algorithm for real-parameter optimization

2013 ◽  
Vol 57 (2) ◽  
pp. 493-516 ◽  
Author(s):  
Yi Xiang ◽  
Yuming Peng ◽  
Yubin Zhong ◽  
Zhenyu Chen ◽  
Xuwen Lu ◽  
...  
Keyword(s):  
Parameter Optimization ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Particle Swarm ◽  
Real Parameter ◽  
Bee Colony

Dynamic Function Optimization by Improved Artificial Bee Colony Algorithm

2014 ◽  
Vol 556-562 ◽  
pp. 3562-3566 ◽  
Author(s):  
Shuo Jiang
Keyword(s):  
Particle Swarm Optimization ◽  
Greedy Algorithm ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Dynamic Environment ◽  
Particle Swarm ◽  
Function Optimization ◽  
Swarm Optimization ◽  
Bee Colony ◽  
Dynamic Function

In this paper, an improved artificial bee colony algorithm (IABC) for dynamic environment optimization has been proposed. As we compared the IABC with greedy algorithm (GA), Particle swarm optimization (PSO) and original artificial bee colony algorithm (ABC), the result of dynamic function optimization shows that the IABC can obtain satisfactory solutions and good tracing performance for dynamic function in time.

Study on Optimal Method for PID Parameter Based on Artificial Bee Colony Algorithm

2014 ◽  
Vol 624 ◽  
pp. 454-459 ◽  
Author(s):  
Guang Chun Li ◽  
Ping Yan ◽  
Sui Er Wang
Keyword(s):  
Control System ◽  
Parameter Optimization ◽  
Artificial Bee Colony Algorithm ◽  
Optimization Problem ◽  
Artificial Bee Colony ◽  
System Research ◽  
Optimal Method ◽  
Bee Colony ◽  
Optimization Control ◽  
Long Time

The PID parameter optimization has been a hot topic of control system research. Artificial bee colony algorithm is used to optimize the PID parameters of control system, and gives the PID parameter optimization process of the traditional artificial bee colony algorithm. Aiming at the optimization problem of long time, the improved artificial bee colony algorithm was put forward. The simulation results show that the improved artificial bee colony algorithm can significantly shorten the time of PID parameter optimization, control and better optimization accuracy.

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