Optimization is rapidly evolving, with significant advances in addressing non-convex models in chemical engineering. The drive for cost-effective, eco-friendly, safe, and manageable processes demands robust strategies.
The book explores classic and emerging techniques, including mathematical programming, metaheuristic methods, and machine learning. It evaluates each approach's pros and cons and discusses future developments while featuring insights from leading researchers in the field.
Kruber, Kai; Kinau, Siv Magdalena; Skiborowski, Mirko: Hybrid optimization methodologies for the design of chemical processes - Book Part in: Optimization in Chemical Engineering. Edt. Gómez-Castro, Fernando Israel; Rico-Ramírez, Vicente: 305-341 (2025).
