Parametric Optimization and Related Topics PDF Download
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Author: Jürgen Guddat
Publisher:
ISBN:
Category : Mathematical optimization
Languages : en
Pages : 412
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Book Description
Author: Jürgen Guddat
Publisher:
ISBN:
Category : Mathematical optimization
Languages : en
Pages : 412
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Mathematical optimization
Languages : en
Pages : 184
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Book Description
Author: Abhijit Gosavi
Publisher: Springer
ISBN: 1489974911
Category : Business & Economics
Languages : en
Pages : 530
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Book Description
Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques – especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: · Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) · Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics · An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata · A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online) and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters – Static Simulation Optimization, Reinforcement Learning and Convergence Analysis – this book is written for researchers and students in the fields of engineering (industrial, systems, electrical and computer), operations research, computer science and applied mathematics.
Author: Efstratios N. Pistikopoulos
Publisher: John Wiley & Sons
ISBN: 1119265193
Category : Mathematics
Languages : en
Pages : 320
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Book Description
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.
Author: Tomas Gal
Publisher: Walter de Gruyter
ISBN: 3110871203
Category : Computers
Languages : en
Pages : 465
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Book Description
Postoptimal Analyses, Parametric Programming, and Related Topics: Degeneracy, Multicriteria Decision Making Redundancy.
Author: Hubertus Th. Jongen
Publisher: Springer Science & Business Media
ISBN: 1402080999
Category : Mathematics
Languages : en
Pages : 436
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Book Description
This volume provides a comprehensive introduction to the theory of (deterministic) optimization. It covers both continuous and discrete optimization. This allows readers to study problems under different points-of-view, which supports a better understanding of the entire field. Many exercises are included to increase the reader's understanding.
Author: Roland Durier
Publisher: Springer Science & Business Media
ISBN: 3642468233
Category : Mathematics
Languages : en
Pages : 369
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Book Description
The main objective of this volume is to provide a presentation and discussion of recent developments in optimization and related fields. Equal emphasis is given to theoretical and practical studies. All the papers in this volume contain original results except two of them which are survey contributions. They deal with a wide range of topics such as optimization and variational inequalities, sensitivity and stability analysis, control theory, convex and nonsmooth analysis, and numerical methods.
Author: Werner Oettli
Publisher: Springer Science & Business Media
ISBN: 3642516823
Category : Business & Economics
Languages : en
Pages : 527
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Book Description
This voluume contains actual contributions to the current research directions in Optimizatiton Theory as well as applications to economic problems and to problems in industrial engineering. Of particular interest are: convex- and Nonsmooth Analysis, Sensitivity Theory, Optimization techniques for nonsmooth and Variational problems, Control Theory and Vector optimization. The volume contains research andsurvey papers. The main benefit is given by a global suruvey of the state ofart of modern Optimization Theory and some typical applications.
Author: Arieh Iserles
Publisher: Cambridge University Press
ISBN: 9780521443562
Category : Mathematics
Languages : en
Pages : 344
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Book Description
Continuing the tradition established with the 1992 volume, this 1993's Acta Numerica presents six invited papers on a broad range of topics from numerical analysis. Papers treat each topic at a level intelligible by any numerical analyst from graduate student to professional.
Author: Diethard Klatte
Publisher: Springer Science & Business Media
ISBN: 0306476169
Category : Mathematics
Languages : en
Pages : 351
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Book Description
Many questions dealing with solvability, stability and solution methods for va- ational inequalities or equilibrium, optimization and complementarity problems lead to the analysis of certain (perturbed) equations. This often requires a - formulation of the initial model being under consideration. Due to the specific of the original problem, the resulting equation is usually either not differ- tiable (even if the data of the original model are smooth), or it does not satisfy the assumptions of the classical implicit function theorem. This phenomenon is the main reason why a considerable analytical inst- ment dealing with generalized equations (i.e., with finding zeros of multivalued mappings) and nonsmooth equations (i.e., the defining functions are not c- tinuously differentiable) has been developed during the last 20 years, and that under very different viewpoints and assumptions. In this theory, the classical hypotheses of convex analysis, in particular, monotonicity and convexity, have been weakened or dropped, and the scope of possible applications seems to be quite large. Briefly, this discipline is often called nonsmooth analysis, sometimes also variational analysis. Our book fits into this discipline, however, our main intention is to develop the analytical theory in close connection with the needs of applications in optimization and related subjects. Main Topics of the Book 1. Extended analysis of Lipschitz functions and their generalized derivatives, including ”Newton maps” and regularity of multivalued mappings. 2. Principle of successive approximation under metric regularity and its - plication to implicit functions.
