Depending on the amount of data to process, file generation may take longer.

If it takes too long to generate, you can limit the data by, for example, reducing the range of years.

Chapter

Download BibTeX

Title

An algorithm for finding shortest path tree using ant colony optimization metaheuristic

Authors

[ 1 ] Katedra Sieci Telekomunikacyjnych i Komputerowych, Wydział Elektroniki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Year of publication

2014

Chapter type

chapter in monograph / paper

Publication language

english

Abstract

EN 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.

Pages (from - to)

317 - 326

DOI

10.1007/978-3-319-01622-1_36

URL

https://link.springer.com/chapter/10.1007/978-3-319-01622-1_36

Book

Image Processing and Communications Challenges 5

Presented on

5th International Conference on Image Processing and Communications, IP&C 2013, 11-13.09.2013, Bydgoszcz, Poland

This website uses cookies to remember the authenticated session of the user. For more information, read about Cookies and Privacy Policy.