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dc.contributor.advisor | Yadavalli, Venkata S. Sarma | |
dc.contributor.author | Boshoff, W.B.K.![]() |
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dc.contributor.other | University of Pretoria. Faculty of Engineering, Built Environment and Information Technology. Dept. of Industrial and Systems Engineering | |
dc.date.accessioned | 2013-02-15T10:11:32Z | |
dc.date.available | 2013-02-15T10:11:32Z | |
dc.date.created | 2012-10 | |
dc.description | Thesis (B Eng. (Industrial and Systems Engineering))--University of Pretoria, 2012. | en_US |
dc.description.abstract | The main objective of the military force of any country is to protect its citizens, resources and leadership. As long as the well-being and survival of the nation is at stake, this may be performed at any cost. Fundamentally, there is a strategy behind the decisions made by the military to station their troops at certain positions to protect the nation. This strategy is of great interest and will be explored in this study. Once this strategy is understood, military stationing decisions can be made under the guidance of a data model, showing mathematically the best place to station troops. The mathematical model inherently draws input from the risk data and economic value data of each location in South Africa. The risk of a location sheds light on the likeliness of an enemy invasion at that position based on proximity, access, and capability, while the economic value portrays the reward an enemy might receive for invasion based on Gross Domestic Product delivered and population density in the area. As the inputs are combined, a deployment need begins to unfurl across the country depicted by dark red spots on color graded maps. Taking into account the position of available military bases, their capacities and strike ranges, troops can be allocated to cover the rising risk patterns. The coverage of this deployment priority is the objective of the linear programming model in MS Excel. The model finds the best possible configuration of troops to bases to best cover the priority maps. The results from this study are the recommended deployment strategies to be followed when analyzing risk and economic value as defined by the scope. It may not directly save money as the amount of troops remain unchanged between scenarios, but will certainly prepare military strategists for informed risk related decisions when the time comes. This study may be broadened in the future for more comprehensive deployment results that includes risk by sea and air strikes. | en_US |
dc.format.extent | 49 pages | en_US |
dc.format.medium | en_US | |
dc.identifier.uri | http://hdl.handle.net/2263/21025 | |
dc.language | en | |
dc.language.iso | en | en_US |
dc.publisher | University of Pretoria. Faculty of Engineering, Built Environment and Information Technology. Dept. of Industrial and Systems Engineering | |
dc.rights | Copyright: University of Pretoria | en_US |
dc.subject | Mini-dissertations (Industrial and Systems Engineering) | en_US |
dc.subject | Incursion risk | en_US |
dc.subject | Economic value | en_US |
dc.subject | Military deployment | en_US |
dc.subject | Optimization model | en_US |
dc.title | Military deployment strategy based on risk of incursion by land and economic value | en_US |
dc.type | Text | en_US |