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008			220601s2020 sz | s |||| 0|eng d
020			_a9783031020896
024	7		_a10.1007/978-3-031-02089-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA402.5 _b2020 EB
100	1		_aBurnak, Baris _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687341
245	1	0	_aIntegrated Process Design and Operational Optimization via Multiparametric Programming _cby Baris Burnak, Nikolaos A. Diangelakis, Efstratios N. Pistikopoulos
250			_a1st edition 2020
264		1	_aCham _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XV, 242 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Engineering Science and Technology _x2690-0327
505	0		_aAcknowledgments -- An Introduction to the Grand Unification of Process Design and Operational Optimization -- Mixed-Integer Dynamic Optimization for Simultaneous Process Design and Control -- PAROC: PARametric Optimization and Control Framework -- Integrating Process Design Optimization and Advanced Model-Based Control Strategies -- Process Scheduling and Control via Multiparametric Programming -- Simultaneous Process Design, Scheduling, and Advanced Model-Based Control -- Bibliography -- Authors' Biographies.
520			_aThis book presents a comprehensive optimization-based theory and framework that exploits the synergistic interactions and tradeoffs between process design and operational decisions that span different time scales. Conventional methods in the process industry often isolate decision making mechanisms with a hierarchical information flow to achieve tractable problems, risking suboptimal, even infeasible operations. In this book, foundations of a systematic model-based strategy for simultaneous process design, scheduling, and control optimization is detailed to achieve reduced cost and improved energy consumption in process systems. The material covered in this book is well suited for the use of industrial practitioners, academics, and researchers. In Chapter 1, a historical perspective on the milestones in model-based design optimization techniques is presented along with an overview of the state-of-the-art mathematical tools to solve the resulting complex problems. Chapters 2 and 3 discuss two fundamental concepts that are essential for the reader. These concepts are (i) mixed integer dynamic optimization problems and two algorithms to solve this class of optimization problems, and (ii) developing a model based multiparametric programming model predictive control. These tools are used to systematically evaluate the tradeoffs between different time-scale decisions based on a single high-fidelity model, as demonstrated on (i) design and control, (ii) scheduling and control, and (iii) design, scheduling, and control problems. We present illustrative examples on chemical processing units, including continuous stirred tank reactors, distillation columns, and combined heat and power regeneration units, along with discussions of other relevant work in the literature for each class of problems.
988			_aSynthesis Collection of Technology_2020
650		7	_2embne _9145705 _aOptimización matemática
650		7	_2embne _9145606 _aControl, Teoría de
700	1		_aDiangelakis, Nikolaos A. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687342
700	1		_aPistikopoulos, Efstratios N. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687343
776	0	8	_iPrinted edition: _z9783031001611
776	0	8	_iPrinted edition: _z9783031009617
776	0	8	_iPrinted edition: _z9783031032172
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02089-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI