Rabbi, FazleAyaz, MuhammadDayupay, Johnry P.Oyebode, Oluwadare JoshuaGido, Nathaniel G.Adhikari, NirmalTabuena, Almighty C.Ajibade, Samuel-Soma M.Bassey, Mbiatke Anthony2023-02-162023-02-162022https://hdl.handle.net/11467/6240https://doi.org/10.1109/ICSGRC55096.2022.9845171Firefly Algorithm (FA) mimics firefly behavior by flashing and attracts them. Firefly's global search mobility is improved for dependable global optimization using chaotic maps in this work. Investigations of benchmark problems with chaotic maps are carried out in depth. The system uses eight separate chaotic maps to fine-tune the firefly's enticing movements. By using planned chaotic transmissions instead of fixed values, the new method beats classic firefly methods. According to statistical data and the success rates of FA, the new algorithms improve the solution's performance and the reliability of global optimality.eninfo:eu-repo/semantics/embargoedAccesschaotic map; firefly algorithm; gaussian map; global optimization; tent mapConference Object8892N/A2-s2.0-8513714096310.1109/ICSGRC55096.2022.9845171