More than 900 million people or one third of world's urban population live in either slum or squatter settlements. In the past decades, international, national and local development agencies have taken several policy actions to address this challenge. Despite these policy efforts, slum-free cities remain a distant goal for many developing countries. It is thus important to investigate the empirical questions related to slum formation for informed policymaking: (i) how do slums form and expand? (ii) where and when are they formed? and (iii) what types of structural changes and/or policy interventions could improve housing conditions for urban poor? This dissertation integrates Discrete Event Simulation (DES), Agent-Based Modeling (ABM) and Geographic Information Systems (GIS) into a single simulation framework, named Slumulation , to explore slum formation dynamics. Slumulation is designed to serve as a decision support tool that could be useful for urban planners and policymakers to experiment with new policy ideas ex-ante in a simulated environment with minimal data requirement. The core of this framework is a linked dynamic model operating at both micro and macro geographical and demographic scales. Slumulation explores the collective effect of many interacting inhabitants of slums as well as non-slums and how their interactions with the spatial environment of the city generate emergent structure of slums at the macro scale. Slumulation is tested with a case study of Ahmedabad, a sixth largest city of India with 41% of its population living in slums.