Please use this identifier to cite or link to this item:
https://hdl.handle.net/10321/5575
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Millham, Richard Charles | - |
dc.contributor.advisor | Agbehadji, Israel Edem | - |
dc.contributor.author | Nketsiah, Richard Nana | en_US |
dc.date.accessioned | 2024-10-08T13:14:31Z | - |
dc.date.available | 2024-10-08T13:14:31Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | https://hdl.handle.net/10321/5575 | - |
dc.description | Submitted in fulfillment of the requirements of the degree of Doctor of Philosophy in Information Technology (IT), Durban University of Technology, Durban, South Africa, 2024. | en_US |
dc.description.abstract | This thesis revolves around the bio-inspired optimisation of a newly formulated cost model tailored for initial installation of a user-specified computer networking infrastructure, motivated by requirements of networking industries, with a focal point on minimising labour costs. The new cost function of this infrastructure installation incorporates essential decision variables related to labour, encompassing the daily requirements and costs of both skilled and unskilled workers, their respective hourly rates, installation hours, and the overall project duration. This deliberate emphasis on labour-centric factors aim to offer nuanced insights into the intricacies of project budgeting and resource allocation. The research critically evaluates the effectiveness of the cost function by examining various factors, such as daily fixed costs, a size and complexity factor tailored to individual scenarios, and a penalty coefficient aimed at ensuring compliance with project schedules. Significantly, the deliberate exclusion of equipment, material, maintenance and operational costs underscores the focused examination of labour-related expenditures, providing a unique contribution to the optimisation landscape within the installation of the user-specified computer networking infrastructure projects. Utilising advanced bio-inspired optimisation techniques, alongside real-world data, this study endeavours to gauge the effectiveness of the new cost model in minimising labour expenses while upholding optimal network performance. The anticipated outcomes of this study extend beyond theoretical contexts to practical implications, providing actionable insights and recommendations for network infrastructure planners. The significance of labour-centric considerations in project planning and design is underscored, providing a more encompassing perspective that aligns with the evolving landscape of modern technological infrastructures. By giving attention to labour-intensive aspects within installation of computer networking infrastructure projects, the thesis aspires to enhance budgeting accuracy and streamline resource allocation processes, thereby fostering more efficient and cost-effective project outcomes. | en_US |
dc.format.extent | 228 p | en_US |
dc.language.iso | en | en_US |
dc.subject | Bio-inspired optimisation | en_US |
dc.subject | Cost model | en_US |
dc.subject.lcsh | Information technology--Cost control | en_US |
dc.subject.lcsh | Cost effectiveness | en_US |
dc.subject.lcsh | Labor costs | en_US |
dc.subject.lcsh | Cost control | en_US |
dc.subject.lcsh | Information networks | en_US |
dc.title | Bio-inspired optimisation of a new cost model for minimising labour costs in computer networking infrastructure | en_US |
dc.type | Thesis | en_US |
dc.description.level | D | en_US |
dc.identifier.doi | https://doi.org/10.51415/10321/5575 | - |
local.sdg | SDG04 | en_US |
local.sdg | SDG09 | en_US |
local.sdg | SDG11 | en_US |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
item.fulltext | With Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.openairetype | Thesis | - |
item.languageiso639-1 | en | - |
Appears in Collections: | Theses and dissertations (Accounting and Informatics) |
Files in This Item:
File | Description | Size | Format | |
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Nketsiah_R_2024.pdf | 1.82 MB | Adobe PDF | View/Open |
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