Raw results of the ESO algorithm

The Electrical Storm Optimization (ESO) algorithm, inspired by the dynamic nature of electrical storms, is a novel population-based metaheuristic that employs three dynamically adjusted parameters: field resistance, intensity, and conductivity. Field resistance assesses the spread of solutions within the search space, reflecting strategy diversity. Field intensity balances the exploration of new territories and the exploitation of promising areas. Field conductivity adjusts the adaptability of the search process, enhancing the algorithm's ability to escape local optima. These adjustments enable ESO to adapt in real-time to various optimization scenarios, steering the search toward potential optima. The ESO's performance was rigorously tested against 65 benchmark problems including the IEEE CEC SOBC 2022 suite and 20 well-known metaheuristics. Results demonstrated ESO's superior performance, particularly in tasks requiring a nuanced balance between exploration and exploitation. Its efficacy is further validated through successful applications in four engineering domains, highlighting its precision, stability, flexibility, and efficiency.