Activity-based travel demand models, which have their theoretical foundation explicitly rooted in the accepted notion that travel is derived from daily activities, offer an attractive, but complex, alternative to the conventional four-step forecasting models. Recent implementations of such approaches via microsimulations have shown promise for practical application of this theoretical construct. I propose a one-year study that develops a framework of an activity-travel microsimulator based on the Household Activity Pattern Problem (HAPP). The structure of the framework is an optimization model that matches both the system and individual household level data. Not only this project would offer the development and related methodological contributions, but also would provide foundations for diverse spectrum of applications such as regional transportation planning and simulations of extreme event, recovery management or adoption of alternative fuel vehicles.