Parametric Optimization and Related Topics PDF Download

Author: Jürgen Guddat
Publisher: Mathematical Research
ISBN: 9783112720929
Category : Mathematics
Languages : en
Pages : 0

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No detailed description available for "Parametric Optimization and Related Topics".

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Languages : en
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ISBN: 9783055003370
Category :
Languages : en
Pages : 400

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Author: Jürgen Guddat
Publisher: De Gruyter Akademie Forschung
ISBN:
Category : Mathematical optimization
Languages : en
Pages : 184

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Author: Jürgen Guddat
Publisher:
ISBN:
Category : Mathematical optimization
Languages : en
Pages : 412

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Author: Efstratios N. Pistikopoulos
Publisher: John Wiley & Sons
ISBN: 1119265185
Category : Mathematics
Languages : en
Pages : 320

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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.

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Category : Mathematical optimization
Languages : en
Pages : 184

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Author: Jürgen Guddat
Publisher:
ISBN: 9789703218776
Category :
Languages : en
Pages : 251

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Author: Alexander M. Rubinov
Publisher: Springer Science & Business Media
ISBN: 147576099X
Category : Computers
Languages : en
Pages : 466

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This volume contains, in part, a selection of papers presented at the sixth Australian Optimization Day Miniconference (Ballarat, 16 July 1999), and the Special Sessions on Nonlinear Dynamics and Optimization and Operations Re search - Methods and Applications, which were held in Melbourne, July 11-15 1999 as a part of the Joint Meeting of the American Mathematical Society and Australian Mathematical Society. The editors have strived to present both con tributed papers and survey style papers as a more interesting mix for readers. Some participants from the meetings mentioned above have responded to this approach by preparing survey and 'semi-survey' papers, based on presented lectures. Contributed paper, which contain new and interesting results, are also included. The fields of the presented papers are very large as demonstrated by the following selection of key words from selected papers in this volume: • optimal control, stochastic optimal control, MATLAB, economic models, implicit constraints, Bellman principle, Markov process, decision-making under uncertainty, risk aversion, dynamic programming, optimal value function. • emergent computation, complexity, traveling salesman problem, signal estimation, neural networks, time congestion, teletraffic. • gap functions, nonsmooth variational inequalities, derivative-free algo rithm, Newton's method. • auxiliary function, generalized penalty function, modified Lagrange func tion. • convexity, quasiconvexity, abstract convexity.