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An improved ant colony optimization for the communication network routing problem

โœ Scribed by Dongming Zhao; Liang Luo; Kai Zhang


Publisher
Elsevier Science
Year
2010
Tongue
English
Weight
308 KB
Volume
52
Category
Article
ISSN
0895-7177

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โœฆ Synopsis


Ant colony optimization (ACO) is a population-based meta-heuristic for combinatorial optimization problems such as the communication network routing problem (CNRP). This paper proposes an improved ant colony optimization (IACO) technique, which adapts a new strategy to update the increased pheromone, called the ant-weight strategy, and a mutation operation, to solve the CNRP. The simulation results for a benchmark problem are reported and they are compared to the simple ant colony optimization (ACO) results.


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a b s t r a c t Ant colony optimization (ACO) routing algorithm is one of adaptive and efficient routing algorithms for mobile ad hoc networks (MANETs). In ACO routing algorithms, ant-like agents traverse the network to search a path from a source to a destination, and lay down pheromone on the path