Is there a computational advantage to representing evaporation rate in ant colony optimization as a gaussian random variable?
Files
Department
Computer Science & Engineering Department
Description
We propose an ACO (Ant Colony Optimization) variation in which the evaporation rate, instead of being constant as is common in standard ACO algorithms, is a Gaussian random variable with non-negligible variance. In experimental results in the context of MAX-MIN Ant System (MMAS) and the Traveling Salesman Problem (TSP), we find that our variation performs considerably better than MMAS when the number of iterations is small, and that its performance is slightly better than MMAS when the number of iterations is large. © 2012 ACM.
Publication Date
8-13-2012
Document Type
Book Chapter
Book Title
GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation
Editors
Terence Soule
ISBN
9781450311779
Publisher
Association for Computing Machinery
City
New York, NY
First Page
1
Last Page
8
Keywords
ant colony optimization, pheromone decay
Recommended Citation
APA Citation
Abdelbar, A.
(2012).Is there a computational advantage to representing evaporation rate in ant colony optimization as a gaussian random variable?. Association for Computing Machinery. , 1-8
https://fount.aucegypt.edu/faculty_book_chapters/4
MLA Citation
Abdelbar, Ashraf M.
Is there a computational advantage to representing evaporation rate in ant colony optimization as a gaussian random variable?. Association for Computing Machinery, 2012.pp. 1-8
https://fount.aucegypt.edu/faculty_book_chapters/4