Session: Optimization and Machine Learning in Chemical Manufacturing

As machine learning advances and becomes more widespread in the Chemical and Energy industries, efficient optimization strategies for data-driven and hybrid models (combining first-principles and data-driven approaches) are increasingly critical. This session invites papers on the application of optimization techniques to models in manufacturing. Topics include practical applications, theoretical advancements, emerging challenges, innovative solutions, algorithm development, and workflow strategies for integrating optimization in industrial processes.