TY - JOUR
T1 - Progresses in pigeon-inspired optimization algorithms
AU - Duan, Haibin
AU - Ye, Fei
N1 - Publisher Copyright:
© 2017, Editorial Department of Journal of Beijing University of Technology. All right reserved.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - In recent years, the bio-inspired intelligent optimization has always been a very popular field of study in intelligence computing and has been widely applied in life science, system science, control science, computer science, management science, sociology and other subjects. The pigeon-inspired optimization (PIO) algorithm is a swarm intelligent optimization algorithm that proposed in recent years, which is inspired by the autonomous homing behavior of pigeons in nature. In this paper, the nature of the pigeons mechanism and flock optimization basic principles are described, and the latest developments of flock optimization model were introduced. The typical applications of unmanned aerial vehicle (UAV) formation, control parameter optimization and image processing were reviewed. Finally, the future development direction was forecasted.
AB - In recent years, the bio-inspired intelligent optimization has always been a very popular field of study in intelligence computing and has been widely applied in life science, system science, control science, computer science, management science, sociology and other subjects. The pigeon-inspired optimization (PIO) algorithm is a swarm intelligent optimization algorithm that proposed in recent years, which is inspired by the autonomous homing behavior of pigeons in nature. In this paper, the nature of the pigeons mechanism and flock optimization basic principles are described, and the latest developments of flock optimization model were introduced. The typical applications of unmanned aerial vehicle (UAV) formation, control parameter optimization and image processing were reviewed. Finally, the future development direction was forecasted.
KW - Landmark operator
KW - Pigeon homing
KW - Pigeon-inspired optimization
UR - https://www.scopus.com/pages/publications/85011277768
U2 - 10.11936/bjutxb2016090003
DO - 10.11936/bjutxb2016090003
M3 - 文献综述
AN - SCOPUS:85011277768
SN - 0254-0037
VL - 43
SP - 1
EP - 7
JO - Beijing Gongye Daxue Xuebao / Journal of Beijing University of Technology
JF - Beijing Gongye Daxue Xuebao / Journal of Beijing University of Technology
IS - 1
ER -