Solving channel borrowing problem with coevolutionary genetic algorithms

Authors:
Krzysztof Gajc;Franciszek Seredynski
Affiliations:
University of Podlasie, Department of Computer Science, Siedlce, Poland;University of Podlasie, Department of Computer Science, Siedlce, Poland and Polish-Japanese Institute of Information Technology, Warsaw, Poland and Institute of Computer Science Polish Academy of ...
Venue:
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Year:
2007

Citing 8
Cited 0

Competitive coevolutionary multi-agent systems: the application to mapping and scheduling problems

Journal of Parallel and Distributed Computing - Special issue on parallel evolutionary computing
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Dynamic Channel Allocation for Real-Time Connections in Highway Macrocellular Networks

Wireless Personal Communications: An International Journal
Observations on Using Genetic-Algorithms for Channel Allocation in Mobile Computing

IEEE Transactions on Parallel and Distributed Systems
The Breeder Genetic Algorithm for Frequency Assignment

PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Loosely Coupled Distributed Genetic Algorithms

PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Improved Genetic Algorithm for Channel Allocation with Channel Borrowing in Mobile Computing

IEEE Transactions on Mobile Computing
Comparing a coevolutionary genetic algorithm for multiobjective optimization

CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02

Quantified Score

Hi-index	0.00

Visualization

Abstract

With increasing number of cellular network users, a problem of optimal use of available radio frequencies becomes serious. Some base stations have free frequencies, while users in other stations are blocked because radio resources run out. In this paper we propose to apply coevolutionary genetic algorithm to find optimal borrowing channel scheme and we compare results with those obtained with use of standard genetic algorithm.