NDLI: MCOA: mutated and self-adaptive cuckoo optimization algorithm

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MCOA: mutated and self-adaptive cuckoo optimization algorithm

Content Provider	Springer Nature Link
Author	Mohseni, Seyed Alireza Wong, Tony Duchaine, Vincent
Copyright Year	2016
Abstract	As with other nature-inspired algorithms, the cuckoo optimization algorithm (COA) produces a population of candidate solutions to find the (near-) optimal solutions to a problem. In this paper, several modifications, including a dynamic mutation operator, are proposed for this algorithm. Design of experiments is employed to determine factors controlling the value of parameters and the target levels of those values to achieve desirable output. The efficiency of the modified COA algorithm is substantiated with the help of several optimization test problems. The results are then compared to other well-known algorithms such as PSO, DE and harmony search using a non-parametric statistical procedure. In order to analyze its effectiveness, the proposed modified COA is applied to a feature selection problem and spacecraft attitude control problem.
Starting Page	21
Ending Page	36
Page Count	16
File Format	PDF
ISSN	18645909
Journal	Evolutionary Intelligence
Volume Number	9
Issue Number	1-2
e-ISSN	18645917
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-04-12
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Evolutionary algorithms (EAs) Cuckoo optimization algorithm (COA) Self-adaptive mutation Design of experiments Multi comparison test Kruskal–Wallis test ApplicationMathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Statistical Physics, Dynamical Systems and Complexity Control, Robotics, Mechatronics Bioinformatics Applications of Mathematics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Cognitive Neuroscience Mathematics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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