Alomoush, WaleedWaleedAlomoushOmar, KhairuddinKhairuddinOmarAlrosan, AyatAyatAlrosanAlomari, Yazan M.Yazan M.AlomariAlbashish, DheebDheebAlbashishAlmomani, AmmarAmmarAlmomani2024-05-292024-05-2920201319-157810.1016/j.jksuci.2018.06.010WOS:000540762100008https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049905712&doi=10.1016%2fj.jksuci.2018.06.010&partnerID=40&md5=55324f64d43b2942211d844b36a70dbfhttps://oarep.usim.edu.my/handle/123456789/12090Firefly Algorithm (FA) is one of the new natural inspired optimization algorithms. It is inspired by the flashing behavior of the fireflies. Firefly algorithm, has some drawbacks such as getting trapped into several local optima, FA parameters are set fixed without change during iterations time. Besides that, it does not memorize or remember the history of any situation for each iteration. In this paper, we propos a firefly photinus algorithm (FPA) based on the initialize mate list to solve problems of trapped into several local optima and remember history of situation to forbidden fireflies movements in mate list (history) during the search process, and propose new absorption parameter r to change the parameters during iterations time which lead to balance between exploration and exploitation, and it controls the dominance area of a lighter firefly during time iterations by reduction or increase r coefficient whether. The experimental results tested on thirteen benchmark functions are selected to evaluate performance of the FPA and to compare it with the standards of the FA and Some FA variants algorithm, it show that FPA algorithm can outperform FA and FA variants algorithm in most of the experiments. (C) 2018 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University.en-USFirefly algorithmNatural inspired optimization algorithmNumerical function optimizationArticle599607325