[1]ZHOU Huan,LI Yu.Cuckoo search algorithm with dynamic inertia weight[J].CAAI Transactions on Intelligent Systems,2015,10(4):645-651.[doi:10.3969/j.issn.1673-4785.201409042]
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Cuckoo search algorithm with dynamic inertia weight

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 10 Number of periods: 2015 4 Page number: 645-651 Column: 学术论文—机器学习 Public date: 2015-08-25
Title:
Cuckoo search algorithm with dynamic inertia weight
Author(s):
ZHOU Huan1;  LI Yu2
1. School of Business Administration, He’nan University, Kaifeng 475004, China;
2. Research Institute of Management Science and Engineering, He’nan University, Kaifeng 475004, China
Keywords:
cuckoo search algorithm; function optimization; Lévy flight; dynamic inertia weight; population size; convergence; complexity; parameter selection
CLC:
TP301.6
DOI:
10.3969/j.issn.1673-4785.201409042
Abstract:
In order to improve the search ability and optimization accuracy of cuckoo search algorithm, the cuckoo search with dynamic inertia weight is proposed. By utilizing the dynamic inertia weight, the improved cuckoo search updates the next nest position based on the former best nest position that has been saved with dynamic inertia weight, which can well balance the relation between population exploration and development capabilities. This paper also has a convergence analysis of the improved cuckoo search by the characteristic equation. The performance of the new method is compared with the basic cuckoo search, particle swarm optimization, ant colony optimization and other algorithms, showing that the improved cuckoo search algorithm can significantly reduce the number of iterations and running time, and can effectively improve the convergence speed and convergence precision.
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