Given the increasing frequency and severity of disasters driven by climate change, the development of effective evacuation plans within disaster management programs takes on growing significance. This thesis introduces a simulation-optimization framework designed to enhance existing optimization methodologies for generating evacuation plans, with a specific focus on addressing tsunami threats. It equips the framework with the capacity to incorporate diverse human behavior aspects into the models.  This framework is based on a general-purpose approach for coupling optimization and simulation, as proposed by  Acar et al. (2009), adapted and applied to the evacuation planning domain. Leveraging the capability of simulations to capture and assess human behavior on an individual level and the optimization methodologies' capacity to identify optimal parameters, this framework provides a versatile foundation to examine diverse aspects of human behavior and to derive an optimal evacuation plan that remains robust in response to the examined human behavior aspects. To evaluate the effectiveness of this framework, the thesis applies it to real-world risk data from an urban neighborhood in Istanbul, in a comprehensive case study. This valuable dataset has been sourced from a project sponsored by The Scientific and Technological Research Council of Turkey (TÜBITAK).