Improved seeker optimization algorithm hybridized with firefly algorithm for constrained optimization problems

摘要: Seeker optimization algorithm is one of the recent swarm intelligence metaheuristics for hard problems. It based on human group search behavior and it was successfully applied to various numerical While seeker proven be successful different specific problems, not properly tested a wide set benchmark functions. Our testing standard well-known functions shows that has serious problems with some types In this paper we introduced modifications control exploitation/exploration balance hybridized elements firefly improved its exploitation capabilities. The alone also exhibits deficiencies. proposed modified only overcame shortcomings original algorithms, but outperformed other state-of-the-art algorithms.