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This paper aims to develop a high-performance method for designing Finite Impulse Response (FIR) filters that effectively control the over-frequency response parameters. The proposed approach involves designing an optimal FIR filter based on an Infinite Impulse Response (IIR) filter, considering various parameters such as pass and stop band ripples, stop band attenuation, transition bandwidth, and linear phase response. The advantages of the IIR filter's better frequency response are utilized in this design. The parameters of Butterworth and Chebyshev filters are optimized using Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) algorithms, incorporating novel fitness functions based on different distance metrics. Visual examination of the filtered signals shows that the proposed algorithm reduces phase delay compared to traditional filters. Additionally, the performance of the designed filter is evaluated by decomposing a sinusoidal signal with four different frequencies into its sub-bands. The numerical results demonstrate that the proposed approach achieves more precise decomposition compared to commonly used traditional filters. [ABSTRACT FROM AUTHOR]