Thesis (Ph.D.) - Cairo University - Faculty o Computers and Information - Department of Information Systems

Spatial Decision Support Systems (SDSSs) are designed to solve spatially problems and give a design for integrating analytical modeling capabilities with Geographic Information System (GIS). GISs are characterized by many attributes that are crucial to SDSS framework, such as having spatial data management and analysis capabilities. they are not considered as SDSS by itself. In addition, GIS has various analysis capabilities to help decision makers in applications of the Spatial Site Selection Problems (SSSPs) for societal, economical, and environmental fields. However,These tools is not sufficient to solve SSSPs. Implementing the associated Multi-Criteria Evaluation (MCE) methods to the GIS leads to a prioritization of the available positions since the MCE analysis methods depend on the tradeoffs among some criteria by developing weights and priorities to give the best solutions. However, it does not lead to an efficient positions.Therefore, the major limitation in GIS structure is the existence of optimization modeling capabilities. That motivation limits the performance of GIS in solving such types of problems. The research team suggest the Multi-Objective Optimization Models to be one of the GIS analysis tools to improve the results produced from GIS in solving the site selection problems and increase the effectiveness of GIS AI techniques will be investigated and will be determined the better one

Issued also as CD