Data-driven inverse optimization (IO) aims to estimate unknown parameters in an
optimization model from observed decisions. The IO problem is commonly formulated as a …

The operational flexibility of a chemical process refers to its ability to maintain feasible
operations despite uncertain deviations from the nominal conditions. It is an important …

Novelty search (NS) refers to a class of exploration algorithms that automatically uncover
diverse system behaviors through simulations or experiments. Systematically obtaining …

The ability to certify feasibility in process design and process operations is crucial in many
applications. This includes quality-by-design in pharmaceutical manufacturing, where a key …

For decades, subspace identification method (SIM) has been widely adopted for modeling
multiple-input multiple-output processes. However, conventional SIMs yield unsatisfactory …

The integrated design and control (IDC) framework is becoming increasingly important for
systematic design of flexible manufacturing and energy systems. Recent advances in …