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Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks

Thesis (PhD)--University of Pretoria, 2009.

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Other Authors: Engelbrecht, Andries P.
Format: Thesis
Published: University of Pretoria 2013
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access_status_str Open Access
author2 Engelbrecht, Andries P.
author_browse Engelbrecht, Andries P.
author_facet Engelbrecht, Andries P.
collection Thesis
dc_rights_str_mv © 2009, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Thesis (PhD)--University of Pretoria, 2009.
format Thesis
id oai:repository.up.ac.za:2263/28233
institution University of Pretoria (South Africa)
last_indexed 2026-06-10T12:38:34.370Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2013
publishDateRange 2013
publishDateSort 2013
publisher University of Pretoria
publisherStr University of Pretoria
record_format dspace
source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/28233 Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks Engelbrecht, Andries P. salmank@kfupm.edu.sa Khan, S.A. (Salman Ahmad) Stochastic evolution Swarm intelligence Simulated evolution Fuzzy logic Unified and-or operator Optimization Local area networks Simulated annealing Ant colony optimization Particle swarm optimization (PSO) UCTD Thesis (PhD)--University of Pretoria, 2009. Topology design of distributed local area networks (DLANs) can be classified as an NP-hard problem. Intelligent algorithms, such as evolutionary and swarm intelligence techniques, are candidate approaches to address this problem and to produce desirable solutions. DLAN topology design consists of several conflicting objectives such as minimization of cost, minimization of network delay, minimization of the number of hops between two nodes, and maximization of reliability. It is possible to combine these objectives in a single-objective function, provided that the trade-offs among these objectives are adhered to. This thesis proposes a strategy and a new aggregation operator based on fuzzy logic to combine the four objectives in a single-objective function. The thesis also investigates the use of a number of evolutionary algorithms such as stochastic evolution, simulated evolution, and simulated annealing. A number of hybrid variants of the above algorithms are also proposed. Furthermore, the applicability of swarm intelligence techniques such as ant colony optimization and particle swarm optimization to topology design has been investigated. All proposed techniques have been evaluated empirically with respect to their algorithm parameters. Results suggest that simulated annealing produced the best results among all proposed algorithms. In addition, the hybrid variants of simulated annealing, simulated evolution, and stochastic evolution generated better results than their respective basic algorithms. Moreover, a comparison of ant colony optimization and particle swarm optimization shows that the latter generated better results than the former. Computer Science unrestricted 2013-09-07T13:05:53Z 2009-10-08 2013-09-07T13:05:53Z 2009-09-02 2009-10-08 2009-09-27 Thesis Khan, SA 2009, Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks, PhD thesis, University of Pretoria, Pretoria, viewed yymmdd < http://hdl.handle.net/2263/28233 > D678/ag http://hdl.handle.net/2263/28233 http://upetd.up.ac.za/thesis/available/etd-09272009-153908/ © 2009, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf University of Pretoria
spellingShingle Stochastic evolution
Swarm intelligence
Simulated evolution
Fuzzy logic
Unified and-or operator
Optimization
Local area networks
Simulated annealing
Ant colony optimization
Particle swarm optimization (PSO)
UCTD
Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks
title Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks
title_full Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks
title_fullStr Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks
title_full_unstemmed Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks
title_short Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks
title_sort design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks
topic Stochastic evolution
Swarm intelligence
Simulated evolution
Fuzzy logic
Unified and-or operator
Optimization
Local area networks
Simulated annealing
Ant colony optimization
Particle swarm optimization (PSO)
UCTD
url http://hdl.handle.net/2263/28233
http://upetd.up.ac.za/thesis/available/etd-09272009-153908/