Paper Info
Title
Is there a computational advantage to representing evaporation rate in ant colony optimization as a gaussian random variable?
Abstract
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.
Year
DOI
Venue
2012
10.1145/2330163.2330165
GECCO
Keywords
Field
DocType
computational advantage,evaporation rate,ant colony optimization,non-negligible variance,standard aco algorithm,gaussian random variable,max-min ant system,salesman problem,traveling salesman problem
Ant colony optimization algorithms,Normal distribution,Mathematical optimization,Evaporation,Computer science,Travelling salesman problem,Artificial intelligence,Machine learning
Conference
Citations 
PageRank 
References 
3
0.40
8
Authors
1
Name
Order
Citations
PageRank
Ashraf M. Abdelbar124325.43