Bölükbaşı, Gizem2017-08-252017-08-252017-072017-072017-08-21http://hdl.handle.net/11693/33557Cataloged from PDF version of article.Thesis (M.S.): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2017.Includes bibliographical references (leaves 51-58).The lack of access to electricity in developing countries necessitates spatial electricity planning for guiding sustainable electri cation projects that evaluate the costs of centralized systems vis-a-vis decentralized approaches. Heuristic approaches have been widely used in such electri cation problems to nd feasible, cost e ective solutions; however, most of the time global optimality of these solutions is not guaranteed. Our thesis through its modeling approach provides a new methodology to nd the least cost solution to this electri cation problem. We model the spatial network planning problem as Prize Collecting Steiner Tree problem which would be base for a decision support tool for rural electri cation. This new method is systematically assessed using both randomly generated data and real data from rural regions across Sub- Saharan Africa. Comparative results for the proposed approach and a widely used heuristic method are presented based on computational experiments. Additionally, a bi-objective approach that permits to take carbon emission level into the account is implemented and experimented with numerical data.xi, 64 leaves : charts ; 29 cm.Englishinfo:eu-repo/semantics/openAccessEnergy Infrastructure PlanningGridIsolated SystemsRural Electri cationMinimum Spanning TreeSpatial Electricity PlanningPrize Collecting Steiner TreeSub-Saharan AfricaBi-objective OptimizationThesisB156109