At any given time people around the world are adversely a ected by the impact of current
or recent disasters. This is increasingly true as increase in population density, population
migration, and technological development amplify the severity, and in some cases the
frequency, of disasters.
The number of people killed in disasters is estimated to be three to four times higher
in developing countries than in the developed ones and the number a ected is estimated
to be forty times higher in the former. In addition, the severity of the consequences
is also higher. The objective of disaster response in the humanitarian relief chain is to
rapidly provide relief to areas a ected by large-scale emergencies, so as to minimise human
su ering and death.
This project focused on nding an appropriate way to determine the required number
of pre-positioned emergency supply warehouses and adequate locations to place these
warehouses in order to enable the quick movement of the required aid supplies from these
facilities to areas in Southern African Development Communities (SADC) a ected by the
occurrence of disasters.
To achieve this, a Maximal Covering Location Problem (MCLP), that includes spatial
objects rather than single points, partial coverage, and weights assigned to disaster areas,
was used to suggest potential locations for warehouses in SADC that will maximise the
coverage of the more disaster-prone areas. The problem was subsequently solved, still
using spatial objects and the same weights, but without partial coverage, to compare and
validate the results of the models.
Thesis (B Eng. (Industrial and Systems Engineering))--University of Pretoria, 2010.