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
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