Fruit Fly Optimization Algorithm Based on Single-Gene Mutation for High-Dimensional Unconstrained Optimization Problems
Joint Authors
Guo, Xiao-dong
Zhang, Xue-liang
Wang, Li-fang
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-17
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
The fruit fly optimization (FFO) algorithm is a new swarm intelligence optimization algorithm.
In this study, an adaptive FFO algorithm based on single-gene mutation, named AFFOSM, is designed to aim at inefficiency under all-gene mutation mode when solving the high-dimensional optimization problems.
The use of a few adaptive strategies is core to the AFFOSM algorithm, including any given population size, mutation modes chosen by a predefined probability, and variation extents changed with the optimization progress.
At first, an offspring individual is reproduced from historical best fruit fly individual, namely, elite reproduction mechanism.
And then either uniform mutation or Gauss mutation happens by a predefined probability in a randomly selected gene.
Variation extent is dynamically changed with the optimization progress.
The simulation results show that AFFOSM algorithm has a better accuracy of convergence and capability of global search than the ESSMER algorithm and several improved versions of the FFO algorithm.
American Psychological Association (APA)
Guo, Xiao-dong& Zhang, Xue-liang& Wang, Li-fang. 2020. Fruit Fly Optimization Algorithm Based on Single-Gene Mutation for High-Dimensional Unconstrained Optimization Problems. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1202399
Modern Language Association (MLA)
Guo, Xiao-dong…[et al.]. Fruit Fly Optimization Algorithm Based on Single-Gene Mutation for High-Dimensional Unconstrained Optimization Problems. Mathematical Problems in Engineering No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1202399
American Medical Association (AMA)
Guo, Xiao-dong& Zhang, Xue-liang& Wang, Li-fang. Fruit Fly Optimization Algorithm Based on Single-Gene Mutation for High-Dimensional Unconstrained Optimization Problems. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1202399
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202399