Liang Zeng1,2, Mai Hu1, Chenning Zhang1, Quan Yuan1, Shanshan Wang1,2,*
CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1677-1709, 2024, DOI:10.32604/cmc.2024.049717
Abstract Optimization algorithms play a pivotal role in enhancing the performance and efficiency of systems across various scientific and engineering disciplines. To enhance the performance and alleviate the limitations of the Northern Goshawk Optimization (NGO) algorithm, particularly its tendency towards premature convergence and entrapment in local optima during function optimization processes, this study introduces an advanced Improved Northern Goshawk Optimization (INGO) algorithm. This algorithm incorporates a multifaceted enhancement strategy to boost operational efficiency. Initially, a tent chaotic map is employed in the initialization phase to generate a diverse initial population, providing high-quality feasible solutions. Subsequently, after… More >
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