TY - JOUR
T1 - Design and development of a unified framework towards swarm intelligence
AU - Zhang, Shuzhu
AU - Lee, C. K. M.
AU - Yu, K. M.
AU - Lau, H. C. W.
PY - 2017
Y1 - 2017
N2 - The application of swarm intelligence (SI) in the optimization field has been gaining much popularity, and various SI algorithms have been proposed in last decade. However, with the increased number of SI algorithms, most research focuses on the implementation of a specific choice of SI algorithms, and there has been rare research analyzing the common features among SI algorithms coherently. More importantly, no general principles for the implementation and improvement of SI algorithms exist for solving various optimization problems. In this research, aiming to cover such a research gap, a unified framework towards SI is proposed inspired by the in-depth analysis of SI algorithms. The unified framework consists of the most frequently used operations and strategies derived from typical examples of SI algorithms. Following the proposed unified framework, the intrinsic features of SI algorithms can be understood straightforwardly and the implementation and improvement of SI algorithms can be achieved effortlessly, which is of great importance in practice. The numerical experiments examine the effects of the possible strategies employed in the unified framework, and provide pilot attempts to validate the performance of different combinations of strategies, which can not only facilitate specific SI algorithm application, but also can motivate SI algorithm innovation.
AB - The application of swarm intelligence (SI) in the optimization field has been gaining much popularity, and various SI algorithms have been proposed in last decade. However, with the increased number of SI algorithms, most research focuses on the implementation of a specific choice of SI algorithms, and there has been rare research analyzing the common features among SI algorithms coherently. More importantly, no general principles for the implementation and improvement of SI algorithms exist for solving various optimization problems. In this research, aiming to cover such a research gap, a unified framework towards SI is proposed inspired by the in-depth analysis of SI algorithms. The unified framework consists of the most frequently used operations and strategies derived from typical examples of SI algorithms. Following the proposed unified framework, the intrinsic features of SI algorithms can be understood straightforwardly and the implementation and improvement of SI algorithms can be achieved effortlessly, which is of great importance in practice. The numerical experiments examine the effects of the possible strategies employed in the unified framework, and provide pilot attempts to validate the performance of different combinations of strategies, which can not only facilitate specific SI algorithm application, but also can motivate SI algorithm innovation.
KW - algorithms
KW - optimization
KW - swarm intelligence
UR - http://handle.uws.edu.au:8081/1959.7/uws:35667
U2 - 10.1007/s10462-016-9481-y
DO - 10.1007/s10462-016-9481-y
M3 - Article
SN - 1573-7462
SN - 0269-2821
VL - 47
SP - 253
EP - 277
JO - Artificial Intelligence Review
JF - Artificial Intelligence Review
IS - 2
ER -