DocumentCode :
2469412
Title :
An improved ant colony optimization for communication network routing problem
Author :
Zhao, Dongming ; Luo, Liang ; Zhang, Kai
Author_Institution :
Sch. of Electron. Eng. & Comput. Sci., Peking Univ., Beijing, China
fYear :
2009
fDate :
16-19 Oct. 2009
Firstpage :
1
Lastpage :
4
Abstract :
Ant colony optimization (ACO) is a population-based meta-heuristic for combinatorial optimization problems such as communication network routing problem (CNRP). This paper proposes an improved ant colony optimization (IACO), which adapts a new strategy to update the increased pheromone, called ant-weight strategy, and a mutation operation, to solve CNRP. The simulation result for a benchmark problem is reported and compared to the simple ant colony optimization (ACO).
Keywords :
optimisation; telecommunication network routing; ant colony optimization; ant-weight strategy; combinatorial optimization problem; communication network routing problem; mutation operation; population-based metaheuristic; Algorithm design and analysis; Ant colony optimization; Communication networks; Concurrent computing; Constraint optimization; DNA computing; Design optimization; Encoding; Routing; Sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing, 2009. BIC-TA '09. Fourth International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3866-2
Electronic_ISBN :
978-1-4244-3867-9
Type :
conf
DOI :
10.1109/BICTA.2009.5338074
Filename :
5338074
Link To Document :
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