Integration of planning, scheduling, and control of no-wait batch plant

The batch process plays an important role in industrial production. Among them, production processes that have specific requirements for operational continuity in each processing stage should consider the no-wait constraint to meet the production reality. The batch process with a no-wait constraint is a typical NP-hard problem. In this work, we propose a framework for the integration of planning, scheduling, and control. We also propose a decomposition method with an improved genetic algorithm to solve the integration problem of scheduling and control for the no-wait batch process. The integrated formulation represents a typical mixed-logic dynamic optimization (MLDO) problem, which involves logical disjunctions and operational dynamics. Then, we address the integrated problem as a grey-box optimization problem, using data-driven feasibility analysis and surrogate models to approximate the unknown black-box constraints. Finally, we test specific production instances to demonstrate the feasibility and superiority of the proposed integration model of the no-wait batch process and optimization algorithm.