Recent Progress of Swarm Intelligent Optimization Algorithms

Swarm intelligent optimization algorithm is a kind of optimization algorithm that simulates the behavior characteristics of biological groups in nature. It has the advantages of strong global searching ability, strong adaptability, strong parallelism, and easy implementation. Swarm intelligent optimization algorithm is a bio-inspired algorithm, which faces the challenges of convergence speed, parameter sensitivity, and robustness when solving complex optimization problems. In recent years, in the field of swarm intelligence optimization algorithms, researchers have proposed a series of new swarm intelligence optimization algorithms. The newly proposed six-swarm intelligent optimization algorithms and its variant models and applications are reviewed, and experiments are carried out on CEC2020 test function. The convergence accuracy and stability of these six swarm intelligent optimization algorithms are evaluated comprehensively, and the future development trend of swarm intelligent optimization algorithms is briefly described. © 2024 Journal of Computer Engineering and Applications Beijing Co., Ltd.; Science Press. All rights reserved.