yashar2026-01-292026-01-2917.12.2025https://hdl.handle.net/20.500.12695/3987With the growing demand for high-speed optimization algorithms, particularly for complex and time sensitive problems, developing an effective high-speed metaheuristic approach presents a significant challenge in this field. This paper introduces a novel metaheuristic method aimed at enhancing both speed and efficiency in solving optimization problems, especially the binary knapsack problem. The simulation results reveal that the proposed algorithm significantly outperforms Genetic Algorithms (GA) and Imperialist Competitive Algorithms (ICA) in addressing the binary knapsack problem. Notably, the high convergence speed of this new method not only enhances its effectiveness but also establishes it as a highly efficient option for tackling complex and time-critical optimization challenges.eninfo:eu-repo/semantics/embargoedAccessConference Object