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Erschienen in:
Cooperative Model of Evolutionary Algorithms and Real-World Problems Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

Channel Assignment with Ant Colony Optimization

verfasst von : Marko Peras, Nikola Ivkovic

Erschienen in: Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing

Verlag: Springer International Publishing

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Abstract

In wireless communication arise various forms of optimization problems including channel assignment problem. There are many possible ways to assign channels to wireless links and our goal is to find the assignment that minimizes channel interference. For that purpose we have developed an ant colony optimization algorithm based on general guidelines of MAX-MIN Ant System and implemented it in C++ language. The algorithm was tested on problem instances and the results showed that the proposed algorithm is learning about instances that is solving and that way improves solution quality with the increase of iterations. Results confirmed that the proposed algorithm is an appropriate approach for solving channel assignment problem in cellular networks.

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Vorheriges Kapitel Population Size in Differential Evolution
Nächstes Kapitel Self-organizing Migrating Algorithm with Non-binary Perturbation
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Metadaten
Titel
Channel Assignment with Ant Colony Optimization
verfasst von
Marko Peras
Nikola Ivkovic
Copyright-Jahr
2020
Buch
Swarm, Evolutionary, and Memetic Computing and Fuzzy and Neural Computing

Print ISBN: 978-3-030-37837-0

Electronic ISBN: 978-3-030-37838-7

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-37838-7_4