An Analytical Framework for Runtime of a Class of Continuous Evolutionary Algorithms
Joint Authors
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-12
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Although there have been many studies on the runtime of evolutionary algorithms in discrete optimization, relatively few theoretical results have been proposed on continuous optimization, such as evolutionary programming (EP).
This paper proposes an analysis of the runtime of two EP algorithms based on Gaussian and Cauchy mutations, using an absorbing Markov chain.
Given a constant variation, we calculate the runtime upper bound of special Gaussian mutation EP and Cauchy mutation EP.
Our analysis reveals that the upper bounds are impacted by individual number, problem dimension number n, searching range, and the Lebesgue measure of the optimal neighborhood.
Furthermore, we provide conditions whereby the average runtime of the considered EP can be no more than a polynomial of n.
The condition is that the Lebesgue measure of the optimal neighborhood is larger than a combinatorial calculation of an exponential and the given polynomial of n.
American Psychological Association (APA)
Zhang, Yushan& Hu, Guiwu. 2015. An Analytical Framework for Runtime of a Class of Continuous Evolutionary Algorithms. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1057706
Modern Language Association (MLA)
Zhang, Yushan& Hu, Guiwu. An Analytical Framework for Runtime of a Class of Continuous Evolutionary Algorithms. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1057706
American Medical Association (AMA)
Zhang, Yushan& Hu, Guiwu. An Analytical Framework for Runtime of a Class of Continuous Evolutionary Algorithms. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1057706
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057706