A Hybrid Genetic Algorithm and Sperm Swarm Optimization (HGASSO) for Multimodal Functions

In this paper, we propose a hybrid algorithm combining two different metaheuristic methods, “Genetic Algorithms (GA)” and “Sperm Swarm Optimization (SSO)”, for the global optimization of multimodal benchmarks functions. The proposed Hybrid Genetic Algorithm Sperm (HGASSO) operates based on incorporates concepts from GA SSO in which generates individuals new iteration not only by crossover mutation operations as GA, but also techniques local search SSO. main idea behind hybridization is to reduce probability trapping optimum multi modal problem. Our compared against algorithms. experimental results using suite functions taken literature have evinced superiority HGASSO approach over other approaches terms quality convergence rates obtained good solving that include cosine, sine, exponent their formulation.