This chapter presents a formal framework for applying Ideal Traffic Assignment (ITA) to transportation policy and planning. The methodology transitions policy formulation from an intuitive process to a quantitative, optimizable procedure. It introduces a systematic classification of network variables, distinguishing the roles of planning from forecasting. The framework defines policies as a combination of primitive “atomic” transformations on a network’s mathematical structure, which can be combined to form complex “molecular” policies. This approach enables the rigorous analysis and synthesis of policy interventions. It also facilitates a two-step optimization process: generating a finite set of feasible policies and then evaluating them based on a user-defined goal function. The framework’s core strength lies in its ability to simulate and predict the systemic effects of policy changes on network performance. It provides a powerful, data-efficient tool for urban planners.