Multi-Parametric Optimization and Control - (Wiley Operations Research and Management Science) (Hardcover)

About the Book

"Multi-parametric programming is a type of mathematical optimization where the optimization problem is solved as a function of multiple parameters. Developed in parallel to sensitivity analysis, the idea of solving optimization problems for a range and as a function of certain bounded parameters has gained considerable interest. Within the past 10 years, there have been developments in multiple parameters, integer variables, and nonlinearities. In particular, the connection between parametric programming and model predictive control has contributed to an increased interest in the topic. The diversity of its application, from explicit control over bi-level programming to integration of design, scheduling, and control, stems from theoretical and algorithmic advances in multi-parametric programming. State-of-the-art software tools with novel solution approaches have been implemented for many types of multi-parametric programming problems, including multi-parametric mixed-integer programming, multi-parametric nonlinear programming, and multi-parametric bi- and multi-level programming"--

Book Synopsis

Recent developments in multi-parametric optimization and control

Multi-Parametric Optimization and Control provides comprehensive coverage of recent methodological developments for optimal model-based control through parametric optimization. It also shares real-world research applications to support deeper understanding of the material.

Researchers and practitioners can use the book as reference. It is also suitable as a primary or a supplementary textbook. Each chapter looks at the theories related to a topic along with a relevant case study. Topic complexity increases gradually as readers progress through the chapters. The first part of the book presents an overview of the state-of-the-art multi-parametric optimization theory and algorithms in multi-parametric programming. The second examines the connection between multi-parametric programming and model-predictive control--from the linear quadratic regulator over hybrid systems to periodic systems and robust control.

The third part of the book addresses multi-parametric optimization in process systems engineering. A step-by-step procedure is introduced for embedding the programming within the system engineering, which leads the reader into the topic of the PAROC framework and software platform. PAROC is an integrated framework and platform for the optimization and advanced model-based control of process systems.

• Uses case studies to illustrate real-world applications for a better understanding of the concepts presented
• Covers the fundamentals of optimization and model predictive control
• Provides information on key topics, such as the basic sensitivity theorem, linear programming, quadratic programming, mixed-integer linear programming, optimal control of continuous systems, and multi-parametric optimal control

An appendix summarizes the history of multi-parametric optimization algorithms. It also covers the use of the parametric optimization toolbox (POP), which is comprehensive software for efficiently solving multi-parametric programming problems.

From the Back Cover

Recent developments in Multi-Parametric Optimization and Control

Multi-Parametric Optimization and Control provides comprehensive coverage of recent theoretical, algorithmic and computational developments in multi-parametric optimization and control for different types of optimization problems, and their application to different classes of optimal model-based control problems. This book presents an overview of the state-of-the-art multi-parametric optimization theory and algorithms in multi-parametric programming and it examines the connection between multi-parametric programming and model-predictive control. Ideal for academics, researchers, and control and optimization practitioners, this excellent resource:

• Uses case studies to illustrate real-world applications for a better understanding of the concepts presented
• Covers the fundamentals of optimization and model predictive control by multi-parametric programming
• Provides information on key topics, such as the basic sensitivity theorem, linear programming, quadratic programming, mixed-integer linear programming, optimal control of continuous systems, and multi-parametric optimal control

An appendix summarizes the history of multi-parametric optimization algorithms. It also covers the use of the parametric optimization toolbox (POP), which is comprehensive state-of-the-art software for efficiently solving multi-parametric programming problems.

About the Author

EFSTRATIOS N. PISTIKOPOULOS is the Director of the Texas A&M Energy Institute and a TEES Eminent Professor in the Artie McFerrin Department of Chemical Engineering at Texas A&M University. He holds a Ph.D. degree from Carnegie Mellon University (1988) and was with Shell Chemicals in Amsterdam before joining Imperial. He has authored or co-authored over 500 major research publications in the areas of modelling, control and optimization of process, energy and systems engineering applications, 15 books and 2 patents.

NIKOLAOS A. DIANGELAKIS is an Optimization Specialist at Octeract Ltd. He holds a PhD and MSc on Advanced Chemical Engineering from Imperial College London and was a member of the Multi-Parametric Optimization and Control group at Imperial and then Texas A&M since 2011. He is the co-author of 16 journal papers, 11 conference papers and 3 book chapters.

RICHARD OBERDIECK is a Technical Account Manager at Gurobi Optimization, LLC. He obtained a bachelor and MSc degrees from ETH Zurich in Switzerland (2009-1013), before pursuing a PhD in Chemical Engineering at Imperial College London, UK, which he completed in 2017. He has published 21 papers and 2 book chapters, has an h-index of 11 and was awarded the FICO Decisions Award 2019 in Optimization, Machine Learning and AI.