A unified theory and framework for the integration of process design, control, and scheduling based on a single high fidelity model is presented. The framework features (i) a mixed-integer dynamic optimization (MIDO) formulation with design, scheduling, and control considerations, and (ii) a multiparametric optimization strategy for the derivation of offline/explicit maps of optimal receding horizon policies. Explicit model predictive control schemes are developed as a function of design and scheduling decisions, and similarly design dependent scheduling policies are derived accounting for the closed-loop dynamics. Inherent multi-scale gap issues are addressed by an offline design dependent surrogate model. The proposed framwork is illustrated by two example problems, a system of two continuous stirred tank reactor, and a small residential combined heat and power (CHP) network. (C) 2019 Elsevier Ltd. All rights reserved.