Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Operations Research and Decision Support

Location allocation decision of special facilities in healthcare is a topic that is gaining continuous attention especially in developing countries. Given the high cost of such facilities and the need to provide healthcare-related services for as many service seekers as possible, systematic methods are needed to handle such a problem. The main purpose of this thesis is to develop an algorithm that solves the capacitated maximal covering location problem which is used to model the mentioned problem. First, a model was developed to solve the problem in hand then, in order to capture more realistic factors related to the location allocation model, two main modifications were applied. The first is to add a second objective function for minimizing total traveled distance besides the main objective function of maximizing the demand coverage. The second modification is to develop a simulation optimization model that considers the stochastic aspects of demand for specialized healthcare services. A modified two-loop particle swarm optimization is proposed to solve the problem and is then altered to handle the first modification introduced. It is further combined with fast non-dominated sorting technique to deal with the multi-objective aspects of the model. Finally, the transition from deterministic to probabilistic demand is implemented by integrating Monte Carlo simulation with the proposed algorithm

Issued also as CD