Investigation of Slime Mould Algorithm and Hybrid Slime Mould Algorithms' Performance in Global Optimization Problems

The Slime mould algorithm (SMA) is a relatively new metaheuristic technique that was just presented. While the performance of newly proposed algorithms gives satisfactory results in optimization problems, combining recently with components different improves SMAs. In recent years, leader SMA (LSMA) and equilibrium optimizer (ESMA) methods, which combined algorithms, have been proposed. advantages two methods over problems are shown. this study, order to eliminate disadvantages SMA, such as slow convergence rate local optimum, performances CEC2020 test functions were investigated together LSMA ESMA years. obtained statistically analyzed given detail study.