Lectures On Stochastic Programming
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Lectures On Stochastic Programming
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Author : Alexander Shapiro
language : en
Publisher:
Release Date : 2021
Lectures On Stochastic Programming written by Alexander Shapiro and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Stochastic programming categories.
"This third edition covers optimization problems involving uncertain parameters, for which stochastic models are available"--
An Introduction To Convexity Optimization And Algorithms
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Author : Heinz H. Bauschke
language : en
Publisher: SIAM
Release Date : 2023-12-20
An Introduction To Convexity Optimization And Algorithms written by Heinz H. Bauschke and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-20 with Mathematics categories.
This concise, self-contained volume introduces convex analysis and optimization algorithms, with an emphasis on bridging the two areas. It explores cutting-edge algorithms—such as the proximal gradient, Douglas–Rachford, Peaceman–Rachford, and FISTA—that have applications in machine learning, signal processing, image reconstruction, and other fields. An Introduction to Convexity, Optimization, and Algorithms contains algorithms illustrated by Julia examples and more than 200 exercises that enhance the reader’s understanding of the topic. Clear explanations and step-by-step algorithmic descriptions facilitate self-study for individuals looking to enhance their expertise in convex analysis and optimization. Designed for courses in convex analysis, numerical optimization, and related subjects, this volume is intended for undergraduate and graduate students in mathematics, computer science, and engineering. Its concise length makes it ideal for a one-semester course. Researchers and professionals in applied areas, such as data science and machine learning, will find insights relevant to their work.
Introduction To Nonlinear Optimization
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Author : Amir Beck
language : en
Publisher: SIAM
Release Date : 2023-06-29
Introduction To Nonlinear Optimization written by Amir Beck and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-29 with Mathematics categories.
Built on the framework of the successful first edition, this book serves as a modern introduction to the field of optimization. The author’s objective is to provide the foundations of theory and algorithms of nonlinear optimization as well as to present a variety of applications from diverse areas of applied sciences. Introduction to Nonlinear Optimization gradually yet rigorously builds connections between theory, algorithms, applications, and actual implementation. The book contains several topics not typically included in optimization books, such as optimality conditions in sparsity constrained optimization, hidden convexity, and total least squares. Readers will discover a wide array of applications such as circle fitting, Chebyshev center, the Fermat–Weber problem, denoising, clustering, total least squares, and orthogonal regression. These applications are studied both theoretically and algorithmically, illustrating concepts such as duality. Python and MATLAB programs are used to show how the theory can be implemented. The extremely popular CVX toolbox (MATLAB) and CVXPY module (Python) are described and used. More than 250 theoretical, algorithmic, and numerical exercises enhance the reader's understanding of the topics. (More than 70 of the exercises provide detailed solutions, and many others are provided with final answers.) The theoretical and algorithmic topics are illustrated by Python and MATLAB examples. This book is intended for graduate or advanced undergraduate students in mathematics, computer science, electrical engineering, and potentially other engineering disciplines.
Stochastic Programming
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Author : V.V. Kolbin
language : en
Publisher: Springer Science & Business Media
Release Date : 1977-06-30
Stochastic Programming written by V.V. Kolbin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1977-06-30 with Computers categories.
This book is devoted to the problems of stochastic (or probabilistic) programming. The author took as his basis the specialized lectures which he delivered to the graduates from the economic cybernetics department of Leningrad University beginning in 1967. Since 1971 the author has delivered a specialized course on Stochastic Programming to the gradu ates from the faculty of applied mathematics/management processes at Leningrad University. The present monograph consists of seven chapters. In Chapter I, which is of an introductory character, consideration is given to the problems of uncertainty and probability, used for modelling complicated systems. Fundamental indications for the classification of stochastic pro gramming problems are given. Chapter II is devoted to the analysis of various models of chance-constrained stochastic programming problems. Examples of technological and applied economic problems of management with chance-constraints are given. In Chapter III two-stage stochastic programming problems are investigated, various models are given, and these models are qualitatively analyzed. In the conclusion of the chapter consideration is given to: the transport problem with random data, the problem of the determination of production volume, and the problem of planning the flights of aircraft as two-stage stochastic programming problems. Multi-stage stochastic programming problems are investigated in Chapter IV. The dependencies between prior and posterior decision rules and decision distributions are given. Dual problems are investigated.
Problems And Solutions For Integer And Combinatorial Optimization
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Author : Mustafa Ç. Pınar
language : en
Publisher: SIAM
Release Date : 2023-11-10
Problems And Solutions For Integer And Combinatorial Optimization written by Mustafa Ç. Pınar and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-10 with Mathematics categories.
The only book offering solved exercises for integer and combinatorial optimization, this book contains 102 classroom tested problems of varying scope and difficulty chosen from a plethora of topics and applications. It has an associated website containing additional problems, lecture notes, and suggested readings. Topics covered include modeling capabilities of integer variables, the Branch-and-Bound method, cutting planes, network optimization models, shortest path problems, optimum tree problems, maximal cardinality matching problems, matching-covering duality, symmetric and asymmetric TSP, 2-matching and 1-tree relaxations, VRP formulations, and dynamic programming. Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization is meant for undergraduate and beginning graduate students in mathematics, computer science, and engineering to use for self-study and for instructors to use in conjunction with other course material and when teaching courses in discrete optimization.
Moment And Polynomial Optimization
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Author : Jiawang Nie
language : en
Publisher: SIAM
Release Date : 2023-06-15
Moment And Polynomial Optimization written by Jiawang Nie and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-15 with Mathematics categories.
Moment and polynomial optimization is an active research field used to solve difficult questions in many areas, including global optimization, tensor computation, saddle points, Nash equilibrium, and bilevel programs, and it has many applications. The author synthesizes current research and applications, providing a systematic introduction to theory and methods, a comprehensive approach for extracting optimizers and solving truncated moment problems, and a creative methodology for using optimality conditions to construct tight Moment-SOS relaxations. This book is intended for applied mathematicians, engineers, and researchers entering the field. It can be used as a textbook for graduate students in courses on convex optimization, polynomial optimization, and matrix and tensor optimization.
Modern Nonconvex Nondifferentiable Optimization
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Author : Ying Cui
language : en
Publisher: SIAM
Release Date : 2021-12-02
Modern Nonconvex Nondifferentiable Optimization written by Ying Cui and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-02 with Mathematics categories.
Starting with the fundamentals of classical smooth optimization and building on established convex programming techniques, this research monograph presents a foundation and methodology for modern nonconvex nondifferentiable optimization. It provides readers with theory, methods, and applications of nonconvex and nondifferentiable optimization in statistical estimation, operations research, machine learning, and decision making. A comprehensive and rigorous treatment of this emergent mathematical topic is urgently needed in today’s complex world of big data and machine learning. This book takes a thorough approach to the subject and includes examples and exercises to enrich the main themes, making it suitable for classroom instruction. Modern Nonconvex Nondifferentiable Optimization is intended for applied and computational mathematicians, optimizers, operations researchers, statisticians, computer scientists, engineers, economists, and machine learners. It could be used in advanced courses on optimization/operations research and nonconvex and nonsmooth optimization.
Practical Nonconvex Nonsmooth Optimization
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Author : Frank E. Curtis
language : en
Publisher: SIAM
Release Date : 2025-12-05
Practical Nonconvex Nonsmooth Optimization written by Frank E. Curtis and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-05 with Mathematics categories.
This book provides a clear and accessible introduction to an important class of problems in mathematical optimization: those involving continuous functions that may be nonconvex, nonsmooth, or both. The authors begin with an intuitive treatment of theoretical foundations, including properties of nonconvex and nonsmooth functions and conditions for optimality. They then offer a broad overview of the most effective and efficient algorithms for solving such problems, with a focus on practical applications in areas such as control systems, signal processing, and data science. Practical Nonconvex Nonsmooth Optimization focuses on problems in finite-dimensional real-vector spaces, avoiding the need for a background in functional analysis. It introduces concepts through nonconvex smooth optimization, making the material more accessible to those without extensive experience in convex analysis. A conversational tone is used throughout, with technical proofs placed at the end of each chapter to help readers understand the core ideas before engaging with detailed arguments. This book is intended for advanced undergraduates and graduate students who are familiar with basic optimization concepts and are ready to explore more complex problems. A background in calculus, real analysis, linear algebra, and probability is recommended. It is appropriate for an introductory graduate-level course in continuous optimization. Practitioners and early career researchers will also find the book useful.
Evaluation Complexity Of Algorithms For Nonconvex Optimization
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Author : Coralia Cartis
language : en
Publisher: SIAM
Release Date : 2022-07-06
Evaluation Complexity Of Algorithms For Nonconvex Optimization written by Coralia Cartis and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-06 with Mathematics categories.
A popular way to assess the “effort” needed to solve a problem is to count how many evaluations of the problem functions (and their derivatives) are required. In many cases, this is often the dominating computational cost. Given an optimization problem satisfying reasonable assumptions—and given access to problem-function values and derivatives of various degrees—how many evaluations might be required to approximately solve the problem? Evaluation Complexity of Algorithms for Nonconvex Optimization: Theory, Computation, and Perspectives addresses this question for nonconvex optimization problems, those that may have local minimizers and appear most often in practice. This is the first book on complexity to cover topics such as composite and constrained optimization, derivative-free optimization, subproblem solution, and optimal (lower and sharpness) bounds for nonconvex problems. It is also the first to address the disadvantages of traditional optimality measures and propose useful surrogates leading to algorithms that compute approximate high-order critical points, and to compare traditional and new methods, highlighting the advantages of the latter from a complexity point of view. This is the go-to book for those interested in solving nonconvex optimization problems. It is suitable for advanced undergraduate and graduate students in courses on advanced numerical analysis, data science, numerical optimization, and approximation theory.
Quantum Algorithms For Optimizers
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Author : Giacomo Nannicini
language : en
Publisher: SIAM
Release Date : 2025-12-17
Quantum Algorithms For Optimizers written by Giacomo Nannicini and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-17 with Mathematics categories.
This book presents a self-contained introduction to quantum algorithms, with a focus on quantum optimization—quantum approaches to solving optimization problems. It equips readers with the essential tools to assess the strengths and limitations of these algorithms, emphasizing provable guarantees and computational complexity. The first comprehensive treatment of quantum optimization, Quantum Algorithms for Optimizers provides a rigorous introduction to the computational model of quantum computers and to the theory of quantum algorithms, contains detailed discussions of some of the most important developments in quantum optimization algorithms, and summarizes the most significant advances in the open literature. This book is intended for researchers and graduate students in applied mathematics or engineering who are interested in learning about quantum algorithms and quantum optimization. It is also suitable for advanced undergraduates with a comparable background. No prior knowledge of quantum mechanics is assumed.