Weimin Zheng, Mingchao Si, Xiao Sui, Shuchuan Chu, Jengshyang Pan*
CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2173-2196, 2023, DOI:10.32604/cmes.2023.019890
Abstract The meta-heuristic algorithm is a global probabilistic search algorithm for the iterative solution. It has good performance in global optimization fields such as maximization. In this paper, a new adaptive parameter strategy and a parallel communication strategy are proposed to further improve the Cuckoo Search (CS) algorithm. This strategy greatly improves the convergence speed and accuracy of the algorithm and strengthens the algorithm’s ability to jump out of the local optimal. This paper compares the optimization performance of Parallel Adaptive Cuckoo Search (PACS) with CS, Parallel Cuckoo Search (PCS), Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Grey Wolf Optimizer… More >
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