AFSA-SLnO variants for enhanced global optimization

• Main Authors: Norazian, Subari, Junita, Mohamad-Saleh, Noorazliza, Sulaiman
• Format: Conference or Workshop Item
• Language: English; English
• Published: Springer Science and Business Media Deutschland GmbH 2022
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General); TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/39634/1/AFSA-SLnO%20Variants%20for%20Enhanced%20Global%20Optimization.pdf; http://umpir.ump.edu.my/id/eprint/39634/2/AFSA-SLnO%20variants%20for%20enhanced%20global%20optimization_ABS.pdf; http://umpir.ump.edu.my/id/eprint/39634/; https://doi.org/10.1007/978-981-16-8129-5_79

Artificial fish swarm algorithm (AFSA) is a strategy which imitates the natural behavior of fish swarm in the real environment. Many improvements and modifications have been proposed on AFSA to improve its optimization performance. To date, nevertheless, the existing algorithms are still unable to a...