TY - GEN
T1 - Particle Swarm Optimization with Gaussian Disturbance-based Elite Population for Single-objective Problem
AU - Zhang, Zhiming
AU - Sui, Qingya
AU - Qi, Lingyu
AU - Song, Yaotong
AU - Gao, Shangce
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Single-objective optimization, especially with con- straints, is the most common class of problems in biology, society, and energy. Among various optimization algorithms, swarm intelligence algorithms is undoubtedly an effective methods to solve this type of problem. In this study, we propose a novel swarm intelligence optimization method, namely GuLo, which adopts Gaussian random disturbance into elite population-based particle swarm optimization, which leads the improvement of local search. Comprehensive experimental results on a typical single-objective constrained optimization problem benchmark shows that GuLo has the outstanding performance than other state-of-the-art meta-heuristic optimization approaches.
AB - Single-objective optimization, especially with con- straints, is the most common class of problems in biology, society, and energy. Among various optimization algorithms, swarm intelligence algorithms is undoubtedly an effective methods to solve this type of problem. In this study, we propose a novel swarm intelligence optimization method, namely GuLo, which adopts Gaussian random disturbance into elite population-based particle swarm optimization, which leads the improvement of local search. Comprehensive experimental results on a typical single-objective constrained optimization problem benchmark shows that GuLo has the outstanding performance than other state-of-the-art meta-heuristic optimization approaches.
KW - Meta-heuristic
KW - Optimization problem
KW - Swarm intelligence algorithm
UR - http://www.scopus.com/inward/record.url?scp=85186070332&partnerID=8YFLogxK
U2 - 10.1109/ITAIC58329.2023.10408765
DO - 10.1109/ITAIC58329.2023.10408765
M3 - 会議への寄与
AN - SCOPUS:85186070332
T3 - IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)
SP - 1357
EP - 1361
BT - IEEE ITAIC 2023 - IEEE 11th Joint International Information Technology and Artificial Intelligence Conference
A2 - Xu, Bing
A2 - Mou, Kefen
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023
Y2 - 8 December 2023 through 10 December 2023
ER -