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In the given text, it describes a novel approach called the Hybrid PSO GSA Algorithm. This algorithm is a combination of two well-known population-based algorithms, namely Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). The primary objective of this algorithm is to merge the exploitation capability of PSO with the exploration capability of GSA, thereby harnessing the strengths of both algorithms. To evaluate the performance of the proposed hybrid algorithm, several benchmark test functions are utilized to compare it with the standard PSO and GSA algorithms in terms of evolving the best solution. This comparative analysis helps in assessing the effectiveness and efficiency of the hybrid approach.