A Genetic Optimization Algorithm Based on Adaptive Dimensionality Reduction
Joint Authors
Kuang, Tai
Hu, Zhongyi
Xu, Minghai
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-11
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
With the rise of big data in cloud computing, many optimization problems have gradually developed into high-dimensional large-scale optimization problems.
In order to address the problem of dimensionality in optimization for genetic algorithms, an adaptive dimensionality reduction genetic optimization algorithm (ADRGA) is proposed.
An adaptive vector angle factor is introduced in the algorithm.
When the angle of an individual’s adjacent dimension is less than the angle factor, the value of the smaller dimension is marked as 0.
Then, the angle between each individual dimension is calculated separately, and the number of zeros in the population is updated.
When the number of zeros of all individuals in a population exceeds a given constant in a certain dimension, the dimension is considered to have no more information and deleted.
Eight high-dimensional test functions are used to verify the proposed adaptive dimensionality reduction genetic optimization algorithm.
The experimental results show that the convergence, accuracy, and speed of the proposed algorithm are better than those of the standard genetic algorithm (GA), the hybrid genetic and simulated annealing algorithm (HGSA), and the adaptive genetic algorithm (AGA).
American Psychological Association (APA)
Kuang, Tai& Hu, Zhongyi& Xu, Minghai. 2020. A Genetic Optimization Algorithm Based on Adaptive Dimensionality Reduction. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1201467
Modern Language Association (MLA)
Kuang, Tai…[et al.]. A Genetic Optimization Algorithm Based on Adaptive Dimensionality Reduction. Mathematical Problems in Engineering No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1201467
American Medical Association (AMA)
Kuang, Tai& Hu, Zhongyi& Xu, Minghai. A Genetic Optimization Algorithm Based on Adaptive Dimensionality Reduction. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1201467
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201467