Parameter Selection for Ant Colony Algorithm Based on Bacterial Foraging Algorithm
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-12-29
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The optimal performance of the ant colony algorithm (ACA) mainly depends on suitable parameters; therefore, parameter selection for ACA is important.
We propose a parameter selection method for ACA based on the bacterial foraging algorithm (BFA), considering the effects of coupling between different parameters.
Firstly, parameters for ACA are mapped into a multidimensional space, using a chemotactic operator to ensure that each parameter group approaches the optimal value, speeding up the convergence for each parameter set.
Secondly, the operation speed for optimizing the entire parameter set is accelerated using a reproduction operator.
Finally, the elimination-dispersal operator is used to strengthen the global optimization of the parameters, which avoids falling into a local optimal solution.
In order to validate the effectiveness of this method, the results were compared with those using a genetic algorithm (GA) and a particle swarm optimization (PSO), and simulations were conducted using different grid maps for robot path planning.
The results indicated that parameter selection for ACA based on BFA was the superior method, able to determine the best parameter combination rapidly, accurately, and effectively.
American Psychological Association (APA)
Li, Peng& Zhu, Hua. 2016. Parameter Selection for Ant Colony Algorithm Based on Bacterial Foraging Algorithm. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1112457
Modern Language Association (MLA)
Li, Peng& Zhu, Hua. Parameter Selection for Ant Colony Algorithm Based on Bacterial Foraging Algorithm. Mathematical Problems in Engineering No. 2016 (2016), pp.1-12.
https://search.emarefa.net/detail/BIM-1112457
American Medical Association (AMA)
Li, Peng& Zhu, Hua. Parameter Selection for Ant Colony Algorithm Based on Bacterial Foraging Algorithm. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1112457
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112457