Cuckoo Search Algorithm with Dynamic Step and Discovery Probability

Authors

Jingsen Liu, 1. Institute of Intelligent Network System, Henan University, Kaifeng 475004, China;;2. College of Software, Henan University, Kaifeng 475004, China;;
Xiaozhen Liu, 2. College of Software, Henan University, Kaifeng 475004, China;;
Li Yu, 3. Institute of Management Science and Engineering, Henan University, Kaifeng 475004, China;

Abstract

Abstract: In order to further improve the low accuracy and slow convergence speed of algorithm search, a cuckoo search algorithm with dynamic step size and probability of discovery is proposed. The algorithm dynamically constrains the Levy's moving step of each generation by introducing the step adjustment factor, which makes the Levy's flight mechanism adaptive. In the probability of finding, the random inertia weight with uniform distribution and F distribution is used to change the fixed value of the probability of discovery, to strengthen the diversity of the population and to keep the balance between global search and local exploration. The experiment result proves that the proposed algorithm has a good feasibility, and the optimization results and the convergence speed of the algorithm increase.

Recommended Citation

Liu, Jingsen; Liu, Xiaozhen; and Yu, Li (2020) "Cuckoo Search Algorithm with Dynamic Step and Discovery Probability," Journal of System Simulation: Vol. 32: Iss. 2, Article 16.
DOI: 10.16182/j.issn1004731x.joss.17-9093
Available at: https://dc-china-simulation.researchcommons.org/journal/vol32/iss2/16

First Page

289

Revised Date

2018-01-16

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.17-9093

Last Page

298

CLC

TP301.6

Recommended Citation

Liu Jingsen, Liu Xiaozhen, Li Yu. Cuckoo Search Algorithm with Dynamic Step and Discovery Probability[J]. Journal of System Simulation, 2020, 32(2): 289-298.

Corresponding Author

Li Yu,

DOI

10.16182/j.issn1004731x.joss.17-9093