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.
