关键词: 混合自适应布谷鸟算法, 局部搜索策略, 正余弦算子, 全局收敛速度, 群智能算法

Abstract: To enhance the search accuracy and global convergence rate of Cuckoo Search (CS) algorithm,a Hybrid Adaptive Cuckoo algorithm based on Local search strategy (LHACS) was proposed.In this algorithm,a local population was randomly generated around each current solution,the local optimal solution was obtained by sine cosine operator and the current solution was replaced by local optimal solution,which had improved the local search accuracy actually.The adaptive discovery probability and factor of search step were substituted for the fixed ones in CS to enhance the global convergence speed of the algorithm.The experiment of 25 classical high-dimensional benchmark functions showed that the LHACS was superior to CS in convergence rate and search accuracy,and it was applied to engineering optimization design and 0-1 knapsack problems,which verified the validity of the algorithm.

Key words: hybrid adaptive cuckoo search algorithm, local search strategy, sine cosine operator, global convergence speed, swarm intelligence algorithm