Optimizations And Programming PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Optimizations And Programming PDF full book. Access full book title Optimizations And Programming.

Algorithms for Decision Making

Algorithms for Decision Making
Author: Mykel J. Kochenderfer
Publisher: MIT Press
Total Pages: 701
Release: 2022-08-16
Genre: Computers
ISBN: 0262370239

Download Algorithms for Decision Making Book in PDF, ePub and Kindle

A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.


Julia Programming for Operations Research

Julia Programming for Operations Research
Author: Changhyun Kwon
Publisher: Changhyun Kwon
Total Pages: 262
Release: 2019-03-03
Genre: Technology & Engineering
ISBN: 1798205475

Download Julia Programming for Operations Research Book in PDF, ePub and Kindle

Last Updated: December 2020 Based on Julia v1.3+ and JuMP v0.21+ The main motivation of writing this book was to help the author himself. He is a professor in the field of operations research, and his daily activities involve building models of mathematical optimization, developing algorithms for solving the problems, implementing those algorithms using computer programming languages, experimenting with data, etc. Three languages are involved: human language, mathematical language, and computer language. His team of students need to go over three different languages, which requires "translation" among the three languages. As this book was written to teach his research group how to translate, this book will also be useful for anyone who needs to learn how to translate in a similar situation. The Julia Language is as fast as C, as convenient as MATLAB, and as general as Python with a flexible algebraic modeling language for mathematical optimization problems. With the great support from Julia developers, especially the developers of the JuMP—Julia for Mathematical Programming—package, Julia makes a perfect tool for students and professionals in operations research and related areas such as industrial engineering, management science, transportation engineering, economics, and regional science. For more information, visit: http://www.chkwon.net/julia


Convex Optimization

Convex Optimization
Author: Stephen P. Boyd
Publisher: Cambridge University Press
Total Pages: 744
Release: 2004-03-08
Genre: Business & Economics
ISBN: 9780521833783

Download Convex Optimization Book in PDF, ePub and Kindle

Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.


Entropy Optimization and Mathematical Programming

Entropy Optimization and Mathematical Programming
Author: Shu-Cherng Fang
Publisher: Springer Science & Business Media
Total Pages: 364
Release: 1997-07-31
Genre: Business & Economics
ISBN: 9780792399391

Download Entropy Optimization and Mathematical Programming Book in PDF, ePub and Kindle

Entropy optimization is a useful combination of classical engineering theory (entropy) with mathematical optimization. The resulting entropy optimization models have proved their usefulness with successful applications in areas such as image reconstruction, pattern recognition, statistical inference, queuing theory, spectral analysis, statistical mechanics, transportation planning, urban and regional planning, input-output analysis, portfolio investment, information analysis, and linear and nonlinear programming. While entropy optimization has been used in different fields, a good number of applicable solution methods have been loosely constructed without sufficient mathematical treatment. A systematic presentation with proper mathematical treatment of this material is needed by practitioners and researchers alike in all application areas. The purpose of this book is to meet this need. Entropy Optimization and Mathematical Programming offers perspectives that meet the needs of diverse user communities so that the users can apply entropy optimization techniques with complete comfort and ease. With this consideration, the authors focus on the entropy optimization problems in finite dimensional Euclidean space such that only some basic familiarity with optimization is required of the reader.


Optimization Theory and Methods

Optimization Theory and Methods
Author: Wenyu Sun
Publisher: Springer Science & Business Media
Total Pages: 689
Release: 2006-08-06
Genre: Mathematics
ISBN: 0387249761

Download Optimization Theory and Methods Book in PDF, ePub and Kindle

Optimization Theory and Methods can be used as a textbook for an optimization course for graduates and senior undergraduates. It is the result of the author's teaching and research over the past decade. It describes optimization theory and several powerful methods. For most methods, the book discusses an idea’s motivation, studies the derivation, establishes the global and local convergence, describes algorithmic steps, and discusses the numerical performance.


Business Optimization Using Mathematical Programming

Business Optimization Using Mathematical Programming
Author: Josef Kallrath
Publisher: Springer Nature
Total Pages: 653
Release: 2021-08-31
Genre: Business & Economics
ISBN: 3030732371

Download Business Optimization Using Mathematical Programming Book in PDF, ePub and Kindle

This book presents a structured approach to formulate, model, and solve mathematical optimization problems for a wide range of real world situations. Among the problems covered are production, distribution and supply chain planning, scheduling, vehicle routing, as well as cutting stock, packing, and nesting. The optimization techniques used to solve the problems are primarily linear, mixed-integer linear, nonlinear, and mixed integer nonlinear programming. The book also covers important considerations for solving real-world optimization problems, such as dealing with valid inequalities and symmetry during the modeling phase, but also data interfacing and visualization of results in a more and more digitized world. The broad range of ideas and approaches presented helps the reader to learn how to model a variety of problems from process industry, paper and metals industry, the energy sector, and logistics using mathematical optimization techniques.


Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming

Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming
Author: Mohit Tawarmalani
Publisher: Springer Science & Business Media
Total Pages: 492
Release: 2013-04-17
Genre: Mathematics
ISBN: 1475735324

Download Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming Book in PDF, ePub and Kindle

Interest in constrained optimization originated with the simple linear pro gramming model since it was practical and perhaps the only computationally tractable model at the time. Constrained linear optimization models were soon adopted in numerous application areas and are perhaps the most widely used mathematical models in operations research and management science at the time of this writing. Modelers have, however, found the assumption of linearity to be overly restrictive in expressing the real-world phenomena and problems in economics, finance, business, communication, engineering design, computational biology, and other areas that frequently demand the use of nonlinear expressions and discrete variables in optimization models. Both of these extensions of the linear programming model are NP-hard, thus representing very challenging problems. On the brighter side, recent advances in algorithmic and computing technology make it possible to re visit these problems with the hope of solving practically relevant problems in reasonable amounts of computational time. Initial attempts at solving nonlinear programs concentrated on the de velopment of local optimization methods guaranteeing globality under the assumption of convexity. On the other hand, the integer programming liter ature has concentrated on the development of methods that ensure global optima. The aim of this book is to marry the advancements in solving nonlinear and integer programming models and to develop new results in the more general framework of mixed-integer nonlinear programs (MINLPs) with the goal of devising practically efficient global optimization algorithms for MINLPs.


Applied Optimization with MATLAB Programming

Applied Optimization with MATLAB Programming
Author: P. Venkataraman
Publisher: John Wiley & Sons
Total Pages: 546
Release: 2009-03-23
Genre: Technology & Engineering
ISBN: 047008488X

Download Applied Optimization with MATLAB Programming Book in PDF, ePub and Kindle

Technology/Engineering/Mechanical Provides all the tools needed to begin solving optimization problems using MATLAB® The Second Edition of Applied Optimization with MATLAB® Programming enables readers to harness all the features of MATLAB® to solve optimization problems using a variety of linear and nonlinear design optimization techniques. By breaking down complex mathematical concepts into simple ideas and offering plenty of easy-to-follow examples, this text is an ideal introduction to the field. Examples come from all engineering disciplines as well as science, economics, operations research, and mathematics, helping readers understand how to apply optimization techniques to solve actual problems. This Second Edition has been thoroughly revised, incorporating current optimization techniques as well as the improved MATLAB® tools. Two important new features of the text are: Introduction to the scan and zoom method, providing a simple, effective technique that works for unconstrained, constrained, and global optimization problems New chapter, Hybrid Mathematics: An Application, using examples to illustrate how optimization can develop analytical or explicit solutions to differential systems and data-fitting problems Each chapter ends with a set of problems that give readers an opportunity to put their new skills into practice. Almost all of the numerical techniques covered in the text are supported by MATLAB® code, which readers can download on the text's companion Web site www.wiley.com/go/venkat2e and use to begin solving problems on their own. This text is recommended for upper-level undergraduate and graduate students in all areas of engineering as well as other disciplines that use optimization techniques to solve design problems.


Optimization Models

Optimization Models
Author: Giuseppe C. Calafiore
Publisher: Cambridge University Press
Total Pages: 651
Release: 2014-10-31
Genre: Business & Economics
ISBN: 1107050871

Download Optimization Models Book in PDF, ePub and Kindle

This accessible textbook demonstrates how to recognize, simplify, model and solve optimization problems - and apply these principles to new projects.


Optimizations and Programming

Optimizations and Programming
Author: Abdelkhalak El Hami
Publisher: John Wiley & Sons
Total Pages: 290
Release: 2021-05-04
Genre: Technology & Engineering
ISBN: 1848219539

Download Optimizations and Programming Book in PDF, ePub and Kindle

This book is a general presentation of complex systems, examined from the point of view of management. There is no standard formula to govern such systems, nor to effectively understand and respond to them. The interdisciplinary theory of self-organization is teeming with examples of living systems that can reorganize at a higher level of complexity when confronted with an external challenge of a certain magnitude. Modern businesses, considered as complex systems, ideally know how to flexibly and resiliently adapt to their environment, and also how to prepare for change via self-organization. Understanding sources of potential crisis is essential for leaders, though not all crises are necessarily bad news, as creative firms know how to respond to challenges through innovation: new products and markets, organizational learning for collective intelligence, and more.