An Introduction to Optimization

Author: Edwin K. P. Chong,Stanislaw H. Zak

Publisher: John Wiley & Sons

ISBN: 1118515153

Category: Mathematics

Page: 640

View: 1757

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Praise for the Third Edition ". . . guides and leads thereader through the learning path . . . [e]xamples are stated veryclearly and the results are presented with attention todetail." —MAA Reviews Fully updated to reflect new developments in the field, theFourth Edition of Introduction to Optimization fillsthe need for accessible treatment of optimization theory andmethods with an emphasis on engineering design. Basic definitionsand notations are provided in addition to the related fundamentalbackground for linear algebra, geometry, and calculus. This new edition explores the essential topics of unconstrainedoptimization problems, linear programming problems, and nonlinearconstrained optimization. The authors also present an optimizationperspective on global search methods and include discussions ongenetic algorithms, particle swarm optimization, and the simulatedannealing algorithm. Featuring an elementary introduction toartificial neural networks, convex optimization, andmulti-objective optimization, the Fourth Edition alsooffers: A new chapter on integer programming Expanded coverage of one-dimensional methods Updated and expanded sections on linear matrix inequalities Numerous new exercises at the end of each chapter MATLAB exercises and drill problems to reinforce the discussedtheory and algorithms Numerous diagrams and figures that complement the writtenpresentation of key concepts MATLAB M-files for implementation of the discussed theory andalgorithms (available via the book's website) Introduction to Optimization, Fourth Edition is an idealtextbook for courses on optimization theory and methods. Inaddition, the book is a useful reference for professionals inmathematics, operations research, electrical engineering,economics, statistics, and business.

An introduction to optimization

Author: Edwin Kah Pin Chong,Stanislaw H. Żak

Publisher: Wiley-Interscience

ISBN: N.A

Category: Mathematics

Page: 409

View: 3286

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An up-to-date, accessible introduction to an increasingly important field This timely and authoritative book fills a growing need for an introductory text to optimization methods and theory at the senior undergraduate and beginning graduate levels. With consistently accessible and elementary treatment of all topics, An Introduction to Optimization helps students build a solid working knowledge of the field, including unconstrained optimization, linear programming, and constrained optimization. Supplemented with more than one hundred tables and illustrations, an extensive bibliography, and numerous worked-out examples to illustrate both theory and algorithms, this book also provides: A review of the required mathematical background material A mathematical discussion at a level accessible to MBA and business students A treatment of both linear and nonlinear programming An introduction to the most recent developments, including neural networks, genetic algorithms, and the nonsimplex method of Karmarkar A chapter on the use of descent algorithms for the training of feedforward neural networks Exercise problems after every chapter MATLAB exercises and examples An optional solutions manual with MATLAB source listings This book helps students prepare for the advanced topics and technological developments that lie ahead. It is also a useful book for researchers and professionals in mathematics, electrical engineering, economics, statistics, and business.

AN INTRODUCTION TO OPTIMIZATION, 2ND ED

Author: Edwin K.P. Chong,Stanislaw H. Zak

Publisher: N.A

ISBN: 9788126527311

Category:

Page: 496

View: 1628

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Market_Desc: A textbook for a one-semester senior undergraduate or beginning graduate course in optimization theory and methods. Special Features: Features more than 100 tables and illustrations and an extensive bibliography." Treats both linear and nonlinear programming." Includes coverage of recent developments." Exercises and examples in MATLAB. About The Book: " Successful track record. " Impressive author and school backgrounds " Genuine revision plan " Strong reviews

Mathematical Programming

An Introduction to Optimization

Author: Melvyn Jeter

Publisher: Routledge

ISBN: 1351433121

Category: Business & Economics

Page: 360

View: 6011

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First Published in 2018. Routledge is an imprint of Taylor & Francis, an Informa company.

Numerical Analysis and Optimization

An Introduction to Mathematical Modelling and Numerical Simulation

Author: Grégoire Allaire

Publisher: Oxford University Press

ISBN: 0199205213

Category: Mathematics

Page: 455

View: 2882

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This work familiarises students with mathematical models (PDEs) and methods of numerical solution and optimisation. Including numerous exercises and examples, this is an ideal text for advanced students in Applied Mathematics, Engineering, Physical Science and Computer Science.

Engineering Optimization

An Introduction with Metaheuristic Applications

Author: Xin-She Yang

Publisher: John Wiley & Sons

ISBN: 9780470640418

Category: Mathematics

Page: 376

View: 1352

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An accessible introduction to metaheuristics and optimization, featuring powerful and modern algorithms for application across engineering and the sciences From engineering and computer science to economics and management science, optimization is a core component for problem solving. Highlighting the latest developments that have evolved in recent years, Engineering Optimization: An Introduction with Metaheuristic Applications outlines popular metaheuristic algorithms and equips readers with the skills needed to apply these techniques to their own optimization problems. With insightful examples from various fields of study, the author highlights key concepts and techniques for the successful application of commonly-used metaheuristc algorithms, including simulated annealing, particle swarm optimization, harmony search, and genetic algorithms. The author introduces all major metaheuristic algorithms and their applications in optimization through a presentation that is organized into three succinct parts: Foundations of Optimization and Algorithms provides a brief introduction to the underlying nature of optimization and the common approaches to optimization problems, random number generation, the Monte Carlo method, and the Markov chain Monte Carlo method Metaheuristic Algorithms presents common metaheuristic algorithms in detail, including genetic algorithms, simulated annealing, ant algorithms, bee algorithms, particle swarm optimization, firefly algorithms, and harmony search Applications outlines a wide range of applications that use metaheuristic algorithms to solve challenging optimization problems with detailed implementation while also introducing various modifications used for multi-objective optimization Throughout the book, the author presents worked-out examples and real-world applications that illustrate the modern relevance of the topic. A detailed appendix features important and popular algorithms using MATLAB® and Octave software packages, and a related FTP site houses MATLAB code and programs for easy implementation of the discussed techniques. In addition, references to the current literature enable readers to investigate individual algorithms and methods in greater detail. Engineering Optimization: An Introduction with Metaheuristic Applications is an excellent book for courses on optimization and computer simulation at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners working in the fields of mathematics, engineering, computer science, operations research, and management science who use metaheuristic algorithms to solve problems in their everyday work.

An Introduction to Metaheuristics for Optimization

Author: Bastien Chopard,Marco Tomassini

Publisher: Springer

ISBN: 3319930737

Category: Computers

Page: 226

View: 9424

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The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.

An Introduction to Structural Optimization

Author: Peter W. Christensen,A. Klarbring

Publisher: Springer Science & Business Media

ISBN: 1402086660

Category: Technology & Engineering

Page: 214

View: 1297

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This book has grown out of lectures and courses given at Linköping University, Sweden, over a period of 15 years. It gives an introductory treatment of problems and methods of structural optimization. The three basic classes of geometrical - timization problems of mechanical structures, i. e. , size, shape and topology op- mization, are treated. The focus is on concrete numerical solution methods for d- crete and (?nite element) discretized linear elastic structures. The style is explicit and practical: mathematical proofs are provided when arguments can be kept e- mentary but are otherwise only cited, while implementation details are frequently provided. Moreover, since the text has an emphasis on geometrical design problems, where the design is represented by continuously varying—frequently very many— variables, so-called ?rst order methods are central to the treatment. These methods are based on sensitivity analysis, i. e. , on establishing ?rst order derivatives for - jectives and constraints. The classical ?rst order methods that we emphasize are CONLIN and MMA, which are based on explicit, convex and separable appro- mations. It should be remarked that the classical and frequently used so-called op- mality criteria method is also of this kind. It may also be noted in this context that zero order methods such as response surface methods, surrogate models, neural n- works, genetic algorithms, etc. , essentially apply to different types of problems than the ones treated here and should be presented elsewhere.

Cost and Optimization in Government

An Introduction to Cost Accounting, Operations Management, and Quality Control, Second Edition

Author: Aman Khan

Publisher: Routledge

ISBN: 1420067222

Category: Political Science

Page: 382

View: 8261

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The careful management of costs and operations are two of the most essential elements of operating any successful organization, public or private. While the private sector is driven by profit-maximizing incentives to keep costs to a minimum, the public sector’s mission and goals are guided by a different set of objectives: to provide a wide range of essential goods and services to maintain social order, improve public health, revitalize the economy, and, most importantly, to improve the quality of life for its citizens. Although the objectives are different, it is just as important for public decision makers to make the best use of available resources by keeping the cost of operation to a minimum. This book demonstrates that with a careful emphasis on cost accounting, operations management, and quality control, all organizations and governments can increase efficiency, improve performance, and prepare to weather hard times.? This book is divided into three parts: Part I offers thorough coverage of cost fundamentals, with an emphasis on basic cost concepts, cost behavior, cost analysis, cost accounting, and cost control. Part II examines optimization in costs and operations in government including traditional or classical optimization with applications in inventory management and queuing, followed by mathematical programming and network analysis. Finally, Part III explores special topics in cost and optimization, in particular those related to games and decisions, productivity measurement, and quality control. Simple, accessible language and explanations are integrated throughout, and examples have been drawn from government so that readers can easily relate to them. Cost and Optimization in Government is required reading for practicing public managers and students of public administration in need of a clear, concise guide to maximizing public resource efficiency.

An Introduction to Unconstrained Optimisation

Author: J McKeown,D Meegan,D Sprevak

Publisher: CRC Press

ISBN: 9780750300254

Category: Mathematics

Page: 160

View: 7796

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Integrating computer graphics and computer-based exercises with the text, An Introduction to Unconstrained Optimisation illustrates key methods with many examples and exercises using the computer. The book takes an elementary approach to this advanced topic, allowing readers to concentrate on learning and understanding the concepts of numerical optimization without unnecessary involvement in the intricacies of the subject. In addition, the modular approach of the software provides the opportunity to explore the algorithms used and to develop them further or try alternative approaches. Most of the algorithms are based upon a "hill-climbing" concept which, in two dimensions, is illustrated dynamically on the computer screen in the form of contour plots and search directions. The text is not specific to any particular microcomputer. Software is available for the BBC series of machines (40/80 track disc formats) and PC-compatible machines. The software is not available from your local bookstore, but is easily obtainable using the order form in the book. Keeping proofs and lists of methods to a minimum, the book is at a level suitable for a first course in numerical analysis, with a basic knowledge of calculus and vector algebra assumed. This book/software package will be of interest to professionals, teachers, and undergraduate students in mathematics, operational research, science, and engineering as well as economics and management courses that deal with quantitative methods.

Practical Mathematical Optimization

An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms

Author: Jan Snyman

Publisher: Springer Science & Business Media

ISBN: 0387243496

Category: Mathematics

Page: 258

View: 7243

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This book presents basic optimization principles and gradient-based algorithms to a general audience, in a brief and easy-to-read form. It enables professionals to apply optimization theory to engineering, physics, chemistry, or business economics.

Introduction to Optimization Techniques

Fundamentals and Applications of Nonlinear Programming

Author: Masanao Aoki

Publisher: N.A

ISBN: N.A

Category: Mathematics

Page: 335

View: 3325

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Some mathematical preliminaries; Criterion function representation; Location problems; Minimization of unconstrained functions; Minimization of constrained functions; Duality in optimization problems; Comparisons of optimization methods and test problems.

Introduction to Optimization of Structures

Author: N.V. Banichuk

Publisher: Springer Science & Business Media

ISBN: 1461233763

Category: Technology & Engineering

Page: 300

View: 1461

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This is an exposition of the theory, techniques, and the basic formulation of structural optimization problems. The author considers applications of design optimization criteria involving strength, rigidity, stability and weight. Analytic and numerical techniques are introduced for research in optimal shapes and internal configurations of deformable bodies and structures. Problems of the optimal design of beams, systems of rods, plates and shells, are studied in detail. With regard to applications, this work is oriented towards solutions of real problems, such as reduction of the volume or weight of the material, and improvement of mechanical properties of structures. This book is written for readers specializing in applied mechanics, applied mathematics, and numerical analysis."

Elementare Wahrscheinlichkeitstheorie und stochastische Prozesse

Author: Kai L. Chung

Publisher: Springer-Verlag

ISBN: 3642670334

Category: Mathematics

Page: 346

View: 1737

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Aus den Besprechungen: "Unter den zahlreichen Einführungen in die Wahrscheinlichkeitsrechnung bildet dieses Buch eine erfreuliche Ausnahme. Der Stil einer lebendigen Vorlesung ist über Niederschrift und Übersetzung hinweg erhalten geblieben. In jedes Kapitel wird sehr anschaulich eingeführt. Sinn und Nützlichkeit der mathematischen Formulierungen werden den Lesern nahegebracht. Die wichtigsten Zusammenhänge sind als mathematische Sätze klar formuliert." #FREQUENZ#1

An Introduction to Harmony Search Optimization Method

Author: Xiaolei Wang,Xiao-Zhi Gao,Kai Zenger

Publisher: Springer

ISBN: 3319083562

Category: Computers

Page: 88

View: 5269

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This brief provides a detailed introduction, discussion and bibliographic review of the nature1-inspired optimization algorithm called Harmony Search. It uses a large number of simulation results to demonstrate the advantages of Harmony Search and its variants and also their drawbacks. The authors show how weaknesses can be amended by hybridization with other optimization methods. The Harmony Search Method with Applications will be of value to researchers in computational intelligence in demonstrating the state of the art of research on an algorithm of current interest. It also helps researchers and practitioners of electrical and computer engineering more generally in acquainting themselves with this method of vector-based optimization.

Algorithmen - Eine Einführung

Author: Thomas H. Cormen,Charles E. Leiserson,Ronald Rivest,Clifford Stein

Publisher: Walter de Gruyter GmbH & Co KG

ISBN: 3110522012

Category: Computers

Page: 1339

View: 6013

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Der "Cormen" bietet eine umfassende und vielseitige Einführung in das moderne Studium von Algorithmen. Es stellt viele Algorithmen Schritt für Schritt vor, behandelt sie detailliert und macht deren Entwurf und deren Analyse allen Leserschichten zugänglich. Sorgfältige Erklärungen zur notwendigen Mathematik helfen, die Analyse der Algorithmen zu verstehen. Den Autoren ist es dabei geglückt, Erklärungen elementar zu halten, ohne auf Tiefe oder mathematische Exaktheit zu verzichten. Jedes der weitgehend eigenständig gestalteten Kapitel stellt einen Algorithmus, eine Entwurfstechnik, ein Anwendungsgebiet oder ein verwandtes Thema vor. Algorithmen werden beschrieben und in Pseudocode entworfen, der für jeden lesbar sein sollte, der schon selbst ein wenig programmiert hat. Zahlreiche Abbildungen verdeutlichen, wie die Algorithmen arbeiten. Ebenfalls angesprochen werden Belange der Implementierung und andere technische Fragen, wobei, da Effizienz als Entwurfskriterium betont wird, die Ausführungen eine sorgfältige Analyse der Laufzeiten der Programme mit ein schließen. Über 1000 Übungen und Problemstellungen und ein umfangreiches Quellen- und Literaturverzeichnis komplettieren das Lehrbuch, dass durch das ganze Studium, aber auch noch danach als mathematisches Nachschlagewerk oder als technisches Handbuch nützlich ist. Für die dritte Auflage wurde das gesamte Buch aktualisiert. Die Änderungen sind vielfältig und umfassen insbesondere neue Kapitel, überarbeiteten Pseudocode, didaktische Verbesserungen und einen lebhafteren Schreibstil. So wurden etwa - neue Kapitel zu van-Emde-Boas-Bäume und mehrfädigen (engl.: multithreaded) Algorithmen aufgenommen, - das Kapitel zu Rekursionsgleichungen überarbeitet, sodass es nunmehr die Teile-und-Beherrsche-Methode besser abdeckt, - die Betrachtungen zu dynamischer Programmierung und Greedy-Algorithmen überarbeitet; Memoisation und der Begriff des Teilproblem-Graphen als eine Möglichkeit, die Laufzeit eines auf dynamischer Programmierung beruhender Algorithmus zu verstehen, werden eingeführt. - 100 neue Übungsaufgaben und 28 neue Problemstellungen ergänzt. Umfangreiches Dozentenmaterial (auf englisch) ist über die Website des US-Verlags verfügbar.

Introduction to Optimization

Author: Pablo Pedregal

Publisher: Springer Science & Business Media

ISBN: 0387216804

Category: Mathematics

Page: 246

View: 3912

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This undergraduate textbook introduces students of science and engineering to the fascinating field of optimization. It is a unique book that brings together the subfields of mathematical programming, variational calculus, and optimal control, thus giving students an overall view of all aspects of optimization in a single reference. As a primer on optimization, its main goal is to provide a succinct and accessible introduction to linear programming, nonlinear programming, numerical optimization algorithms, variational problems, dynamic programming, and optimal control. Prerequisites have been kept to a minimum, although a basic knowledge of calculus, linear algebra, and differential equations is assumed.