Download or read book Advancing Parametric Optimization written by Nathan Adelgren and published by Springer Nature. This book was released on 2021-01-21 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theory presented in this work merges many concepts from mathematical optimization and real algebraic geometry. When unknown or uncertain data in an optimization problem is replaced with parameters, one obtains a multi-parametric optimization problem whose optimal solution comes in the form of a function of the parameters.The theory and methodology presented in this work allows one to solve both Linear Programs and convex Quadratic Programs containing parameters in any location within the problem data as well as multi-objective optimization problems with any number of convex quadratic or linear objectives and linear constraints. Applications of these classes of problems are extremely widespread, ranging from business and economics to chemical and environmental engineering. Prior to this work, no solution procedure existed for these general classes of problems except for the recently proposed algorithms
Download or read book Parametric Optimization and Approximation written by PARAMETRIC and published by Birkhäuser. This book was released on 2013-11-21 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Non Linear Parametric Optimization written by BANK and published by Birkhäuser. This book was released on 2013-12-21 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multi parametric Optimization and Control written by Efstratios N. Pistikopoulos and published by John Wiley & Sons. This book was released on 2020-11-10 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Simulation Based Optimization written by Abhijit Gosavi and published by Springer. This book was released on 2014-10-30 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Fundamentals of Orthopedic Design with Non parametric Optimization written by Musaddiq Al Ali and published by Springer Nature. This book was released on with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parametric Optimization written by Jürgen Guddat and published by . This book was released on 1990-12-21 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores optimization problems in which some or all of the individual data involved depends on one parameter. Beginning with a preliminary survey of solution algorithms in one-parametric optimization, the text moves on to examine the pathfollowing curves of local minimizers, pathfollowing along a connected component in the Karush-Kuhn-Tucker set and in the critical set, pathfollowing in the set of local minimizers and in the set of critical points. In addition, practical applications are included.
Download or read book Multi parametric Optimization and Control written by Efstratios N. Pistikopoulos and published by John Wiley & Sons. This book was released on 2020-11-24 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Parametric Optimization and Related Topics II written by Jürgen Guddat and published by De Gruyter Akademie Forschung. This book was released on 1991 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Non Linear Parametric Optimization written by B. Bank and published by Walter de Gruyter GmbH & Co KG. This book was released on 1982-12-31 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Non-Linear Parametric Optimization".
Download or read book Multiobjective and Stochastic Optimization Based on Parametric Optimization written by Jürgen Guddat and published by . This book was released on 1985 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Parametric Optimization and Related Topics written by Jürgen Guddat and published by . This book was released on 1987 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Uncertainty aware Integration of Control with Process Operations and Multi parametric Programming Under Global Uncertainty written by Vassilis M. Charitopoulos and published by Springer Nature. This book was released on 2020-02-05 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces models and methodologies that can be employed towards making the Industry 4.0 vision a reality within the process industries, and at the same time investigates the impact of uncertainties in such highly integrated settings. Advances in computing power along with the widespread availability of data have led process industries to consider a new paradigm for automated and more efficient operations. The book presents a theoretically proven optimal solution to multi-parametric linear and mixed-integer linear programs and efficient solutions to problems such as process scheduling and design under global uncertainty. It also proposes a systematic framework for the uncertainty-aware integration of planning, scheduling and control, based on the judicious coupling of reactive and proactive methods. Using these developments, the book demonstrates how the integration of different decision-making layers and their simultaneous optimisation can enhance industrial process operations and their economic resilience in the face of uncertainty.
Download or read book Multi level Mixed Integer Optimization written by Styliani Avraamidou and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-06-06 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the fundamental underlying mathematical theory, numerical algorithms and effi cient computational tools for the solution of multi-level mixedinteger optimization problems. It can enable a vast array of decision makers and engineers (e.g. process engineers, bioengineers, chemical and civil engineers, and economists) to model, formulate and solve hierarchical decision making problems. The book gives detailed insights on multi-level optimization by comprehensive explanations, step-by-step numerical examples and case studies, plots, and diagrams.
Download or read book Post Parametric Automation in Design and Construction written by Alfredo Andia and published by Artech House. This book was released on 2014-11-01 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automation, a mixture of algorithms, robots, software, and avatars, is transforming all types of jobs and industries. This book responds to one critical question for the design and construction industry: “how are architects, engineers, and contractors using information technology to further automate their practices?” Addressing the use of new digital technologies, particularly parametric automation for design and construction in the building industry, this book looks at how technologically advanced architectural and engineering practices are semi-automating their design processes by using sophisticated algorithms to transform their workflows. The book also documents a set of firms that are further advancing automation by using pre-fabrication, modularization, and custom designs via robotics.
Download or read book Advances in Sensitivity Analysis and Parametric Programming written by Tomas Gal and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: The standard view of Operations Research/Management Science (OR/MS) dichotomizes the field into deterministic and probabilistic (nondeterministic, stochastic) subfields. This division can be seen by reading the contents page of just about any OR/MS textbook. The mathematical models that help to define OR/MS are usually presented in terms of one subfield or the other. This separation comes about somewhat artificially: academic courses are conveniently subdivided with respect to prerequisites; an initial overview of OR/MS can be presented without requiring knowledge of probability and statistics; text books are conveniently divided into two related semester courses, with deterministic models coming first; academics tend to specialize in one subfield or the other; and practitioners also tend to be expert in a single subfield. But, no matter who is involved in an OR/MS modeling situation (deterministic or probabilistic - academic or practitioner), it is clear that a proper and correct treatment of any problem situation is accomplished only when the analysis cuts across this dichotomy.
Download or read book Parameter Optimization of Resource Sharing Protocols written by Mark Benedict Bilodeau and published by . This book was released on 1984 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:
