Optimization: A comparison of recent meta-heuristic optimization algorithms using benchmark function

Meta-heuristic optimization algorithms are used in many application areas to solve problems. In recent years, meta-heuristic have gained importance over deterministic search solving However, none of the techniques equally effective all Therefore, researchers focused on either improving current or developing new ones. Many alternative inspired by nature been developed complex It is important compare performances through statistical analysis and determine better algorithm. This paper compares sixteen (AWDA, MAO, TSA, TSO, ESMA, DOA, LHHO, DSSA, LSMA, AOSMA, AGWOCS, CDDO, GEO, BES, LFD, HHO) presented literature between 2021 2022. this context, various test functions, including single-mode, multi-mode, fixed-size multi-mode benchmark were evaluate efficiency used.