TY - GEN
T1 - An Interactive Manta Ray Foraging Optimization Algorithm with Hierarchical Population Structure
AU - Zheng, Tao
AU - Wang, Kaiyu
AU - Li, Jiayi
AU - Todo, Yuki
AU - Gao, Shangce
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The manta ray foraging optimization (MRFO) algorithm is a meta-heuristic method derived by imitating the behavior inspired by manta rays foraging. However, due to the lack of communication among individuals in the population, it suffers from the local optimum trapping problem. In this study, we innovatively propose a hierarchical population structure for it by adding an information interaction layer to the original MRFO population, namely an interactive manta rays foraging optimization (IMRFO) algorithm. In it, the hierarchical population structure successfully realizes the balance between local exploitation and global exploration. The superiority of IMRFO is confirmed in terms of solution quality, convergence speed, population diversity, and search trajectory by experimental findings based on thirty IEEE CEC2017 benchmark functions in comparison with other state-of-the-art meta-heuristic methods.
AB - The manta ray foraging optimization (MRFO) algorithm is a meta-heuristic method derived by imitating the behavior inspired by manta rays foraging. However, due to the lack of communication among individuals in the population, it suffers from the local optimum trapping problem. In this study, we innovatively propose a hierarchical population structure for it by adding an information interaction layer to the original MRFO population, namely an interactive manta rays foraging optimization (IMRFO) algorithm. In it, the hierarchical population structure successfully realizes the balance between local exploitation and global exploration. The superiority of IMRFO is confirmed in terms of solution quality, convergence speed, population diversity, and search trajectory by experimental findings based on thirty IEEE CEC2017 benchmark functions in comparison with other state-of-the-art meta-heuristic methods.
KW - Exploration and exploitation
KW - Manta ray foraging optimization
KW - Meta-heuristic algorithms
KW - Population structure
UR - http://www.scopus.com/inward/record.url?scp=85141198015&partnerID=8YFLogxK
U2 - 10.1109/IHMSC55436.2022.00030
DO - 10.1109/IHMSC55436.2022.00030
M3 - 会議への寄与
AN - SCOPUS:85141198015
T3 - Proceedings - 2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2022
SP - 88
EP - 93
BT - Proceedings - 2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2022
Y2 - 20 August 2022 through 21 August 2022
ER -