A modified adaptive sparrow search algorithm based on chaotic reverse learning and spiral search for global optimization

• Published in: Neural computing & applications Vol. 35; no. 35; pp. 24603 - 24620
• Main Authors: Geng, Junqi, Sun, Xianming, Wang, Haihua, Bu, Xianghai, Liu, Daohuan, Li, Fei, Zhao, Zengwu
• Format: Journal Article
• Language: English
• Published: London Springer London 01.12.2023; Springer Nature B.V
• Subjects: Adaptive algorithms; Adaptive search techniques; Algorithms; Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Convergence; Data Mining and Knowledge Discovery; Exploitation; Global optimization; Heuristic methods; Image Processing and Computer Vision; Probability and Statistics in Computer Science; S.I.: Applications and Techniques in Cyber Intelligence (ATCI2022); Search algorithms; Special Issue on Applications and Techniques in Cyber Intelligence (ATCI2022); Sparrow search algorithm (SSA); Global optimization problems; Swarm-based algorithm; Metaheuristics; Single objective optimization

A population-based metaheuristic algorithm that takes its cues from the foraging strategy of sparrows is called the sparrow search algorithm (SSA). While SSA is competitive when compared to other algorithms, it nevertheless has a propensity to carry out imbalanced exploitation and exploration and fi...