Egyptian Mosquito Optimization Algorithm: A Novel Swarm-based Metaheuristic Algorithm to Solve Electronic and Industrial Problems

This paper pioneers a novel swarm-based metaheuristics algorithm, the Egyptian Mosquito Optimization Algorithm (EMOA), which can be used to solve global optimization problems. The EMOA is inspired by the natural behavior of Egyptian mosquitoes and achieves a balance between exploitation and exploration in the solution search space, effectively tackling optimization challenges. The effectiveness of the EMOA is demonstrated by 23 benchmark functions and the CEC-BC-2017 test suite. According to the analysis of the RMSE values, the RMSE values of the EMOA are 8.5424 and 32.3887 respectively. Finally, the analysis of the exploration and utilization of EMOA in high-dimensional spaces proves that the algorithm has the potential to be a tool for solving high-dimensional optimization problems.