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Risk Averse Optimization And Control
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Book Synopsis Risk-Averse Optimization and Control by : Darinka Dentcheva
Download or read book Risk-Averse Optimization and Control written by Darinka Dentcheva and published by Springer Nature. This book was released on with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Lectures on Stochastic Programming by : Alexander Shapiro
Download or read book Lectures on Stochastic Programming written by Alexander Shapiro and published by SIAM. This book was released on 2009-01-01 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization problems involving stochastic models occur in almost all areas of science and engineering, such as telecommunications, medicine, and finance. Their existence compels a need for rigorous ways of formulating, analyzing, and solving such problems. This book focuses on optimization problems involving uncertain parameters and covers the theoretical foundations and recent advances in areas where stochastic models are available. Readers will find coverage of the basic concepts of modeling these problems, including recourse actions and the nonanticipativity principle. The book also includes the theory of two-stage and multistage stochastic programming problems; the current state of the theory on chance (probabilistic) constraints, including the structure of the problems, optimality theory, and duality; and statistical inference in and risk-averse approaches to stochastic programming.
Book Synopsis Multistage Stochastic Optimization by : Georg Ch. Pflug
Download or read book Multistage Stochastic Optimization written by Georg Ch. Pflug and published by Springer. This book was released on 2014-11-12 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.
Book Synopsis Linear-Quadratic Controls in Risk-Averse Decision Making by : Khanh D. Pham
Download or read book Linear-Quadratic Controls in Risk-Averse Decision Making written by Khanh D. Pham and published by Springer Science & Business Media. This book was released on 2012-10-23 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear-Quadratic Controls in Risk-Averse Decision Making cuts across control engineering (control feedback and decision optimization) and statistics (post-design performance analysis) with a common theme: reliability increase seen from the responsive angle of incorporating and engineering multi-level performance robustness beyond the long-run average performance into control feedback design and decision making and complex dynamic systems from the start. This monograph provides a complete description of statistical optimal control (also known as cost-cumulant control) theory. In control problems and topics, emphasis is primarily placed on major developments attained and explicit connections between mathematical statistics of performance appraisals and decision and control optimization. Chapter summaries shed light on the relevance of developed results, which makes this monograph suitable for graduate-level lectures in applied mathematics and electrical engineering with systems-theoretic concentration, elective study or a reference for interested readers, researchers, and graduate students who are interested in theoretical constructs and design principles for stochastic controlled systems.
Book Synopsis Risk-Averse Capacity Control in Revenue Management by : Christiane Barz
Download or read book Risk-Averse Capacity Control in Revenue Management written by Christiane Barz and published by Springer Science & Business Media. This book was released on 2007-08-02 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book revises the well-known capacity control problem in revenue management from the perspective of a risk-averse decision-maker. Modelling an expected utility maximizing decision maker, the problem is formulated as a risk-sensitive Markov decision process. Special emphasis is put on the existence of structured optimal policies. Numerical examples illustrate the results.
Book Synopsis Nonlinear Optimization by : Andrzej Ruszczynski
Download or read book Nonlinear Optimization written by Andrzej Ruszczynski and published by Princeton University Press. This book was released on 2011-09-19 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is one of the most important areas of modern applied mathematics, with applications in fields from engineering and economics to finance, statistics, management science, and medicine. While many books have addressed its various aspects, Nonlinear Optimization is the first comprehensive treatment that will allow graduate students and researchers to understand its modern ideas, principles, and methods within a reasonable time, but without sacrificing mathematical precision. Andrzej Ruszczynski, a leading expert in the optimization of nonlinear stochastic systems, integrates the theory and the methods of nonlinear optimization in a unified, clear, and mathematically rigorous fashion, with detailed and easy-to-follow proofs illustrated by numerous examples and figures. The book covers convex analysis, the theory of optimality conditions, duality theory, and numerical methods for solving unconstrained and constrained optimization problems. It addresses not only classical material but also modern topics such as optimality conditions and numerical methods for problems involving nondifferentiable functions, semidefinite programming, metric regularity and stability theory of set-constrained systems, and sensitivity analysis of optimization problems. Based on a decade's worth of notes the author compiled in successfully teaching the subject, this book will help readers to understand the mathematical foundations of the modern theory and methods of nonlinear optimization and to analyze new problems, develop optimality theory for them, and choose or construct numerical solution methods. It is a must for anyone seriously interested in optimization.
Book Synopsis Solving Urban Infrastructure Problems Using Smart City Technologies by : John R. Vacca
Download or read book Solving Urban Infrastructure Problems Using Smart City Technologies written by John R. Vacca and published by Elsevier. This book was released on 2020-09-22 with total page 820 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving Urban Infrastructure Problems Using Smart City Technologies is the most complete guide for integrating next generation smart city technologies into the very foundation of urban areas worldwide, showing how to make urban areas more efficient, more sustainable, and safer. Smart cities are complex systems of systems that encompass all aspects of modern urban life. A key component of their success is creating an ecosystem of smart infrastructures that can work together to enable dynamic, real-time interactions between urban subsystems such as transportation, energy, healthcare, housing, food, entertainment, work, social interactions, and governance. Solving Urban Infrastructure Problems Using Smart City Technologies is a complete reference for building a holistic, system-level perspective on smart and sustainable cities, leveraging big data analytics and strategies for planning, zoning, and public policy. It offers in-depth coverage and practical solutions for how smart cities can utilize resident's intellectual and social capital, press environmental sustainability, increase personalization, mobility, and higher quality of life. - Brings together experts from academia, government and industry to offer state-of- the-art solutions for urban system problems, showing how smart technologies can be used to improve the lives of the billions of people living in cities across the globe - Demonstrates practical implementation solutions through real-life case studies - Enhances reader comprehension with learning aid such as hands-on exercises, questions and answers, checklists, chapter summaries, chapter review questions, exercise problems, and more
Book Synopsis Resilient Controls for Ordering Uncertain Prospects by : Khanh D. Pham
Download or read book Resilient Controls for Ordering Uncertain Prospects written by Khanh D. Pham and published by Springer. This book was released on 2014-09-05 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing readers with a detailed examination of resilient controls in risk-averse decision, this monograph is aimed toward researchers and graduate students in applied mathematics and electrical engineering with a systems-theoretic concentration. This work contains a timely and responsive evaluation of reforms on the use of asymmetry or skewness pertaining to the restrictive family of quadratic costs that have been appeared in various scholarly forums. Additionally, the book includes a discussion of the current and ongoing efforts in the usage of risk, dynamic game decision optimization and disturbance mitigation techniques with output feedback measurements tailored toward the worst-case scenarios. This work encompasses some of the current changes across uncertainty quantification, stochastic control communities, and the creative efforts that are being made to increase the understanding of resilient controls. Specific considerations are made in this book for the application of decision theory to resilient controls of the linear-quadratic class of stochastic dynamical systems. Each of these topics are examined explicitly in several chapters. This monograph also puts forward initiatives to reform both control decisions with risk consequences and correct-by-design paradigms for performance reliability associated with the class of stochastic linear dynamical systems with integral quadratic costs and subject to network delays, control and communication constraints.
Book Synopsis Linear and Mixed Integer Programming for Portfolio Optimization by : Renata Mansini
Download or read book Linear and Mixed Integer Programming for Portfolio Optimization written by Renata Mansini and published by Springer. This book was released on 2015-06-10 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents solutions to the general problem of single period portfolio optimization. It introduces different linear models, arising from different performance measures, and the mixed integer linear models resulting from the introduction of real features. Other linear models, such as models for portfolio rebalancing and index tracking, are also covered. The book discusses computational issues and provides a theoretical framework, including the concepts of risk-averse preferences, stochastic dominance and coherent risk measures. The material is presented in a style that requires no background in finance or in portfolio optimization; some experience in linear and mixed integer models, however, is required. The book is thoroughly didactic, supplementing the concepts with comments and illustrative examples.
Book Synopsis Stochastic Programming by : Gerd Infanger
Download or read book Stochastic Programming written by Gerd Infanger and published by Springer Science & Business Media. This book was released on 2010-11-10 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the Preface... The preparation of this book started in 2004, when George B. Dantzig and I, following a long-standing invitation by Fred Hillier to contribute a volume to his International Series in Operations Research and Management Science, decided finally to go ahead with editing a volume on stochastic programming. The field of stochastic programming (also referred to as optimization under uncertainty or planning under uncertainty) had advanced significantly in the last two decades, both theoretically and in practice. George Dantzig and I felt that it would be valuable to showcase some of these advances and to present what one might call the state-of- the-art of the field to a broader audience. We invited researchers whom we considered to be leading experts in various specialties of the field, including a few representatives of promising developments in the making, to write a chapter for the volume. Unfortunately, to the great loss of all of us, George Dantzig passed away on May 13, 2005. Encouraged by many colleagues, I decided to continue with the book and edit it as a volume dedicated to George Dantzig. Management Science published in 2005 a special volume featuring the “Ten most Influential Papers of the first 50 Years of Management Science.” George Dantzig’s original 1955 stochastic programming paper, “Linear Programming under Uncertainty,” was featured among these ten. Hearing about this, George Dantzig suggested that his 1955 paper be the first chapter of this book. The vision expressed in that paper gives an important scientific and historical perspective to the book. Gerd Infanger
Book Synopsis Risk-Sensitive Optimal Control by : Peter Whittle
Download or read book Risk-Sensitive Optimal Control written by Peter Whittle and published by . This book was released on 1990-05-11 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two major themes of this book are risk-sensitive control and path-integral or Hamiltonian formulation. It covers risk-sensitive certainty-equivalence principles, the consequent extension of the conventional LQG treatment and the path-integral formulation.
Book Synopsis First-order and Stochastic Optimization Methods for Machine Learning by : Guanghui Lan
Download or read book First-order and Stochastic Optimization Methods for Machine Learning written by Guanghui Lan and published by Springer Nature. This book was released on 2020-05-15 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.
Book Synopsis Stochastic Programming in Supply Chain Risk Management by : Tadeusz Sawik
Download or read book Stochastic Programming in Supply Chain Risk Management written by Tadeusz Sawik and published by Springer Nature. This book was released on with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimal Control of Switched Systems Arising in Fermentation Processes by : Chongyang Liu
Download or read book Optimal Control of Switched Systems Arising in Fermentation Processes written by Chongyang Liu and published by Springer. This book was released on 2014-09-11 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents, in a systematic manner, the optimal controls under different mathematical models in fermentation processes. Variant mathematical models – i.e., those for multistage systems; switched autonomous systems; time-dependent and state-dependent switched systems; multistage time-delay systems and switched time-delay systems – for fed-batch fermentation processes are proposed and the theories and algorithms of their optimal control problems are studied and discussed. By putting forward novel methods and innovative tools, the book provides a state-of-the-art and comprehensive systematic treatment of optimal control problems arising in fermentation processes. It not only develops nonlinear dynamical system, optimal control theory and optimization algorithms, but can also help to increase productivity and provide valuable reference material on commercial fermentation processes.
Book Synopsis Big Data Management by : Fausto Pedro García Márquez
Download or read book Big Data Management written by Fausto Pedro García Márquez and published by Springer. This book was released on 2016-11-15 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the analytic principles of business practice and big data. Specifically, it provides an interface between the main disciplines of engineering/technology and the organizational and administrative aspects of management, serving as a complement to books in other disciplines such as economics, finance, marketing and risk analysis. The contributors present their areas of expertise, together with essential case studies that illustrate the successful application of engineering management theories in real-life examples.
Book Synopsis Mathematical Optimization for Efficient and Robust Energy Networks by : Natalia Selini Hadjidimitriou
Download or read book Mathematical Optimization for Efficient and Robust Energy Networks written by Natalia Selini Hadjidimitriou and published by Springer Nature. This book was released on 2021-03-19 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of energy production and distribution problems identified by the members of the COST Action TD1207 "Mathematical Optimization in the Decision Support Systems for Efficient and Robust Energy Networks". The aim of the COST Action was to coordinate the efforts of the experts in different fields, from academia and industry, in developing innovative tools for quantitative decision making, and apply them to the efficient and robust design and management of energy networks. The work covers three main goals:• to be a nimble while comprehensive resource of several real life business problems with a categorized set of pointers to many relevant prescriptive problems for energy systems;• to offer a balanced mix of scientific and industrial views;• to evolve over time in a flexible and dynamic way giving, from time to time, a more scientific or industrial - or even political in a broad sense - weighed perspective.It is addressed to researchers and professionals working in the field.
Book Synopsis Supply Chain Disruption Management Using Stochastic Mixed Integer Programming by : Tadeusz Sawik
Download or read book Supply Chain Disruption Management Using Stochastic Mixed Integer Programming written by Tadeusz Sawik and published by Springer. This book was released on 2017-06-30 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains. The problems are modeled using a scenario based stochastic mixed integer programming to address risk-neutral, risk-averse and mean-risk decision-making in the presence of supply chain disruption risks. The book focuses on innovative, computationally efficient portfolio approaches to supply chain disruption management, e.g., selection of primary and recovery supply portfolios, demand portfolios, capacity portfolios, etc. Numerous computational examples throughout the book, modeled in part on real-world supply chain disruption management problems, illustrate the material presented and provide managerial insights. In the computational examples, the proposed mathematical programming models are solved using an advanced algebraic modeling language such as AMPL and CPLEX, GUROBI and XPRESS solvers. The knowledge and tools provided in the book allow the reader to model and solve supply chain disruption management problems using commercially available software for mixed integer programming. Using the end-of chapter problems and exercises, the monograph can also be used as a textbook for an advanced course in supply chain risk management. After an introductory chapter, the book is then divided into five main parts. Part I addresses selection of a supply portfolio; Part II considers integrated selection of supply portfolio and scheduling; Part III looks at integrated, equitably efficient selection of supply portfolio and scheduling; Part IV examines integrated selection of primary and recovery supply (and demand) portfolios and scheduling; and Part V addresses disruption management of information flows in supply chains.