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An Algorithm for Finding Shortest Path Tree Using Ant Colony Optimization Metaheuristic

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Image Processing and Communications Challenges 5

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 233))

Summary

This paper introduces the ShortestPathTreeACO algorithm designed for finding near-optimal and optimal solutions for the shortest path tree problem. The algorithm is based on Ant Colony Optimization metaheuristic, and therefore it is of significant importance to choose proper operation parameters that guarantee the results of required quality. The operation of the algorithm is explained in relation to the pseudocode introduced in the paper. An exemplary execution of the algorithm is depicted and discussed on a step-by-step basis. The experiments carried out within the custom-made framework of the experiment are the source of suggestions concerning the parameter values. The influence of the choice of the number of ants and the pheromone evaporation speed is investigated. The quality of generated solutions is addressed, as well as the issues of execution time.

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Głąbowski, M., Musznicki, B., Nowak, P., Zwierzykowski, P. (2014). An Algorithm for Finding Shortest Path Tree Using Ant Colony Optimization Metaheuristic. In: S. Choras, R. (eds) Image Processing and Communications Challenges 5. Advances in Intelligent Systems and Computing, vol 233. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-01622-1_36

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  • DOI: https://doi.org/10.1007/978-3-319-01622-1_36

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-01621-4

  • Online ISBN: 978-3-319-01622-1

  • eBook Packages: EngineeringEngineering (R0)

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