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Firefly Algorithm Based Optimization Model for Planning of Optical Transport NetworksOLIVEIRA, B. Q.   , SOUSA, M. A. , TELES VIEIRA, F. H. |
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Author keywords
artificial intelligence, communication networks, genetic algorithms, optical fiber networks, optimization
References keywords
networks(21), optical(20), communications(9), algorithm(9), design(7), routing(6), optimization(6), networking(6), network(6), inspired(6)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2020-05-31
Volume 20, Issue 2, Year 2020, On page(s): 55 - 64
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.02007
Web of Science Accession Number: 000537943500007
SCOPUS ID: 85087444683
Abstract
The growth in data traffic is raising serious challenges for OTN in terms of improving their capacity efficiency in order to meet the new traffic requirements. Under these circumstances, the task of efficiently utilizing available resources opens opportunities for the development of a variety of techniques for network planning. This paper presents a decision support system for the optical transport network. It is considered the optical transport network planning problem where a traffic interest matrix between the demand nodes is specified. The network is modeled as a graph, through the arc-path approach. An Integer Linear Programming problem solved with a Firefly Algorithm is proposed for network planning, considering cost minimization. The main novelties of the proposed ILP model is that it accomplishes the optical network design with the possibility of multiple destinations of the traffic matrix and with dynamic allocation of the transmission system modularity. To solve the ILP optimization model the firefly algorithm, genetic algorithm and the exact method are used. Simulations are carried out to verify the performance of the bio-inspired algorithms in relation to the exact method. The results obtained with the firefly algorithm surpass those of the genetic algorithm and approximate the optimal result. |
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
