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About

Mohd Zakree Ahmad Nazri is a computer science researcher whose work centers on swarm intelligence, multi-robot systems, and autonomous path planning. His research focuses on developing and refining bio-inspired optimization algorithms — particularly Particle Swarm Optimization (PSO) — to solve complex real-world challenges in robotics. Among his most notable contributions is his development of hybrid PSO approaches that address fundamental weaknesses in standard swarm algorithms, including premature convergence and poor local search performance. His 2015 paper introducing a hybrid of Modified PSO and local search for multi-robot search systems has accumulated 30 citations, establishing it as a foundational reference in the field. Complementing this, his multi-swarm PSO framework, which employs multiple best particles to enhance exploration in obstacle-laden environments, has drawn a further 15 citations. Nazri has also made valuable contributions to the theoretical landscape through a critical evaluation of robot path planning in dynamic environments, helping researchers navigate the methodological terrain of this evolving discipline. Collectively, his publications reflect a sustained commitment to pushing the boundaries of intelligent robotic navigation, making his work essential reading for students and researchers working at the intersection of swarm intelligence and autonomous robotics.