Mahdi Abdollahi

Islamic Azad University, Tehran, University of Tabriz

Papers

Total Citations

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About

Mahdi Abdollahi is a researcher whose work sits at the intersection of computational intelligence and numerical optimization, with a particular focus on solving complex systems of nonlinear equations. His major contributions center on the development and refinement of metaheuristic algorithms, demonstrating how nature-inspired and population-based methods can be adapted to tackle NP-hard problems that arise across economics, engineering, chemistry, and mechanics. His most cited work, "Improved cuckoo optimization algorithm for solving systems of nonlinear equations" (2016, 21 citations), introduces a novel enhancement to the cuckoo optimization framework, significantly improving its convergence and accuracy for nonlinear systems. In a complementary study, "Multi-population parallel imperialist competitive algorithm for solving systems of nonlinear equations" (2016, 6 citations), he extends the imperialist competitive algorithm by incorporating a parallel, multi-population structure to better explore complex solution landscapes. Together, these contributions highlight Abdollahi’s ability to bridge theoretical algorithm design with practical problem-solving, offering robust tools for researchers and practitioners in applied mathematics and engineering optimization.