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Parameter optimization of Cuckoo Search Algorithm for Multi Dimensional Function Optimization Problem

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Mohammad Shafiul Alam, Samiha Sara Prima, Sanonda Datta Gupta, Jannatun Razia. Published in Algorithms.

Parameter optimization of Cuckoo Search Algorithm for Multi Dimensional Function Optimization Problem
Communications on Applied Electronics
Year of Publication: 2018
Publisher: Foundation of Computer Science (FCS), NY, USA
Series: Volume 7 Number 18
Authors: Mohammad Shafiul Alam, Samiha Sara Prima, Sanonda Datta Gupta, Jannatun Razia
10.5120/cae2018652776
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Mohammad Shafiul Alam, Samiha Sara Prima, Sanonda Datta Gupta and Jannatun Razia. Parameter optimization of Cuckoo Search Algorithm for Multi Dimensional Function Optimization Problem. Communications on Applied Electronics 7(18):6-10, July 2018. BibTeX

@article{10.5120/cae2018652776,
	author = {Mohammad Shafiul Alam and Samiha Sara Prima and Sanonda Datta Gupta and Jannatun Razia},
	title = {Parameter optimization of Cuckoo Search Algorithm for Multi Dimensional Function Optimization Problem},
	journal = {Communications on Applied Electronics},
	issue_date = {July 2018},
	volume = {7},
	number = {18},
	month = {Jul},
	year = {2018},
	issn = {2394-4714},
	pages = {6-10},
	numpages = {5},
	url = {http://www.caeaccess.org/archives/volume7/number18/821-2018652776},
	doi = {10.5120/cae2018652776},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

The Cuckoo Search Algorithm is a recently developed nature inspired meta heuristic algorithm, which is established on the breeding behavior of Cuckoo species. Cuckoo search can be applied on a large variety of optimization problems. The main advantage of this search algorithm is its simplicity and better performance than many other agent or population based meta heuristic algorithms. The algorithm uses only one controlling parameter p, which makes it easier to implement and control. This parameter p, combined with the random walk mutations implemented by Lévy Flights, can control the performance and degree of exploration and exploitation of the algorithm. In this paper we have conducted a few experiments on Cuckoo Search algorithm with Lévy flights to discover the necessary conditions needed for the better performance of the algorithm. For this purpose we have taken different values of the controlling parameter p and observed the performance of the algorithm on benchmark problems, as well as its exploration and exploitation characteristics over different groups of benchmark functions.

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Keywords

Cuckoo search algorithm, function optimization, Lévy flights mutation, parameter optimization.