Buch, Englisch, 464 Seiten, Format (B × H): 170 mm x 240 mm, Gewicht: 774 g
Reihe: De Gruyter graduate
Deterministic, Meta-Heuristic and Data-Driven Techniques
Buch, Englisch, 464 Seiten, Format (B × H): 170 mm x 240 mm, Gewicht: 774 g
Reihe: De Gruyter graduate
ISBN: 978-3-11-138338-5
Verlag: De Gruyter
Optimization is an area in constant evolution. The search for robust optimization techniques to deal with the highly non-convex models that represent the systems related to Chemical Engineering has led to important advances in the area. The need for developing economically feasible processes which are simultaneously environmentally friendly, safe, and controllable requires for adequate optimization strategies. Moreover, finding a global optimum is still a challenge for a diversity of cases. Thus, this book presents a compilation of classic and emerging optimization techniques, focusing on their application to systems related to the Chemical Engineering. The book shows the applications of classic mathematical programming, metaheuristic optimization methods and machine learning-based strategies. The analysis of the described techniques allows the reader identifying the advantages and disadvantages of each approach. Moreover, the book will discuss the perspectives for future developments on the area.
Zielgruppe
Students, Chemical and Process Engineers, Chemists.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
- Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Chemische Verfahrenstechnik
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung




