The research conducted for this thesis uses an agent-based model (ABM) to simulate housing price, location, and journey to work (JTW) times for households in Knox County, Tennessee. The model is a unique hybrid, combining analytic functions and agents that typically have been used separately for theoretical urban research in very simplified urban landscapes. At the same time it uses data from a real urban area to run and calibrate the model, which is common for statistically-based or gravity models. There are two goals for this simulation; first to examine the feasibility of this approach in urban modeling, second to test the effect of altering transportation times and preferences on agent behavior. Results show this approach can fit real data and represent urban processes reasonably well. In addition several interesting and surprising results are reported from model runs.