Cuckoo search algorithm with chaotic maps
type: Item
instance of: scholarly article
title: Cuckoo search algorithm with chaotic maps
zbMATH Open document ID: 1394.90583
DOI: 10.1155/2015/715635
author: Lijin Wang
author: Yiwen Zhong
published in: Mathematical Problems in Engineering
publication date: 2018-08-27T00:00:00Z
review text: Summary: Cuckoo search algorithm is a novel nature-inspired optimization technique based on the obligate brood parasitic behavior of some cuckoo species. It iteratively employs Lévy flights random walk with a scaling factor and biased/selective random walk with a fraction probability. Unfortunately, these two parameters are used in constant value schema, resulting in a problem sensitive to solution quality and convergence speed. In this paper, we proposed a variable value schema cuckoo search algorithm with chaotic maps, called CCS. In CCS, chaotic maps are utilized to, respectively, define the scaling factor and the fraction probability to enhance the solution quality and convergence speed. Extensive experiments with different chaotic maps demonstrate the improvement in efficiency and effectiveness.
Mathematics Subject Classification ID: 90C59
Mathematics Subject Classification ID: 68W25
Mathematics Subject Classification ID: 37D45
zbMATH DE Number: 6927066
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/715635
OpenAlex ID: W1533196493
Wikidata QID: Q59119015
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description: scientific article; zbMATH DE number 6927066