Global optimization models in data networks: a case study

Authors:
M. M. Ali
Affiliations:
School of Computational and Applied Mathematics, Witwatersrand University, Private Bag, WITS Johannesburg, South Africa and Institute for Mathematics and its Applications, University of Minnesota
Venue:
Computers and Operations Research
Year:
2006

Citing 4
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Aspiration Based Simulated Annealing Algorithm

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Population set-based global optimization algorithms: some modifications and numerical studies

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Financial Optimization Models in Data Networks*

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Abstract

In this paper we present a methodology for a rural and semi-urban data network placement. In order to optimally place the network and to ensure that the network is realistic and viable we address four key issues, namely, the demographic and socio-economic issues, geographical estimation, optimization of the network placement and financial optimization. A digital representation of the map of the region where the network has to be placed is used. A continuous optimization algorithm is applied to optimally place the backbone rings, and a combinatorial optimization algorithm is applied to obtain the optimal rollout order for the network. Mathematical formulations for both the optimization problems are presented. Optimal financial indicators are obtained.