Paper Info
Title
ACO vs EAs for solving a real-world frequency assignment problem in GSM networks
Abstract
Frequency planning is a very important task for current GSM operators. In this work we present a new mathematical formulation of the problem in which the frequency plans are evaluated by using accurate interference information coming from a real GSM network. We have developed an ant colony optimization (ACO) algorithm to tackle this problem. After accurately tuning this algorithm, it has been compared against a (1,10) Evolutionary Algorithm (EA). The results show that the ACO clearly outperforms the EA when using different time limits as stopping condition for a rather extensive comparison.
Year
DOI
Venue
2007
10.1145/1276958.1276972
GECCO
Keywords
Field
DocType
important task,ant colony optimization,current gsm operator,real-world frequency assignment problem,extensive comparison,different time limit,evolutionary algorithm,real gsm network,aco vs eas,accurate interference information,frequency plan,frequency planning,evolutionary algorithms
Ant colony optimization algorithms,Frequency assignment problem,GSM,Mathematical optimization,Evolutionary algorithm,Computer science,Artificial intelligence,Operator (computer programming),Interference (wave propagation),Frequency assignment
Conference
Citations 
PageRank 
References 
17
1.10
14
Authors
4
Name
Order
Citations
PageRank
Francisco Luna114412.40
Christian Blum28013.91
Enrique Alba33796242.34
Antonio J. Nebro4111854.62