Engineering Optimization

Theory and Practice

Author: Singiresu S. Rao,S. S. Rao

Publisher: John Wiley & Sons

ISBN: 0470183527

Category: Mathematics

Page: 813

View: 3306

Technology/Engineering/Mechanical Helps you move from theory to optimizing engineering systems in almost any industry Now in its Fourth Edition, Professor Singiresu Rao's acclaimed text Engineering Optimization enables readers to quickly master and apply all the important optimization methods in use today across a broad range of industries. Covering both the latest and classical optimization methods, the text starts off with the basics and then progressively builds to advanced principles and applications. This comprehensive text covers nonlinear, linear, geometric, dynamic, and stochastic programming techniques as well as more specialized methods such as multiobjective, genetic algorithms, simulated annealing, neural networks, particle swarm optimization, ant colony optimization, and fuzzy optimization. Each method is presented in clear, straightforward language, making even the more sophisticated techniques easy to grasp. Moreover, the author provides: Case examples that show how each method is applied to solve real-world problems across a variety of industries Review questions and problems at the end of each chapter to engage readers in applying their newfound skills and knowledge Examples that demonstrate the use of MATLAB® for the solution of different types of practical optimization problems References and bibliography at the end of each chapter for exploring topics in greater depth Answers to Review Questions available on the author's Web site to help readers to test their understanding of the basic concepts With its emphasis on problem-solving and applications, Engineering Optimization is ideal for upper-level undergraduates and graduate students in mechanical, civil, electrical, chemical, and aerospace engineering. In addition, the text helps practicing engineers in almost any industry design improved, more efficient systems at less cost.

Optimization—Theory and Practice

Author: Wilhelm Forst,Dieter Hoffmann

Publisher: Springer Science & Business Media

ISBN: 0387789774

Category: Mathematics

Page: 402

View: 2830

Optimization is a field important in its own right but is also integral to numerous applied sciences, including operations research, management science, economics, finance and all branches of mathematics-oriented engineering. Constrained optimization models are one of the most widely used mathematical models in operations research and management science. This book gives a modern and well-balanced presentation of the subject, focusing on theory but also including algorithims and examples from various real-world applications. Detailed examples and counter-examples are provided--as are exercises, solutions and helpful hints, and Matlab/Maple supplements.

Optimization

Theory and Practice

Author: Mohan C. Joshi,Kannan M. Moudgalya

Publisher: Alpha Science Int'l Ltd.

ISBN: 9781842651964

Category: Computers

Page: 325

View: 4709

Optimization: Theory and Practice is ideally suited for a first course on Optimization. It gives a detailed mathematical exposition to various optimization techniques. The presentation style retains abstract flavor of the mathematical framework as well as applicability potential of techniques, thereby making the text useful to both scientists and engineers. The topics covered are: Single and multi-dimensional optimization, Linear programming, Nonlinear constrained optimization and Evolutionary algorithms

Linear and Integer Optimization

Theory and Practice, Third Edition

Author: Gerard Sierksma,Yori Zwols

Publisher: CRC Press

ISBN: 1498743129

Category: Business & Economics

Page: 686

View: 5317

Presenting a strong and clear relationship between theory and practice, Linear and Integer Optimization: Theory and Practice is divided into two main parts. The first covers the theory of linear and integer optimization, including both basic and advanced topics. Dantzig’s simplex algorithm, duality, sensitivity analysis, integer optimization models, and network models are introduced. More advanced topics also are presented including interior point algorithms, the branch-and-bound algorithm, cutting planes, complexity, standard combinatorial optimization models, the assignment problem, minimum cost flow, and the maximum flow/minimum cut theorem. The second part applies theory through real-world case studies. The authors discuss advanced techniques such as column generation, multiobjective optimization, dynamic optimization, machine learning (support vector machines), combinatorial optimization, approximation algorithms, and game theory. Besides the fresh new layout and completely redesigned figures, this new edition incorporates modern examples and applications of linear optimization. The book now includes computer code in the form of models in the GNU Mathematical Programming Language (GMPL). The models and corresponding data files are available for download and can be readily solved using the provided online solver. This new edition also contains appendices covering mathematical proofs, linear algebra, graph theory, convexity, and nonlinear optimization. All chapters contain extensive examples and exercises. This textbook is ideal for courses for advanced undergraduate and graduate students in various fields including mathematics, computer science, industrial engineering, operations research, and management science.

Introduction to Nonsmooth Optimization

Theory, Practice and Software

Author: Adil Bagirov,Napsu Karmitsa,Marko M. Mäkelä

Publisher: Springer

ISBN: 3319081144

Category: Business & Economics

Page: 372

View: 6849

This book is the first easy-to-read text on nonsmooth optimization (NSO, not necessarily differentiable optimization). Solving these kinds of problems plays a critical role in many industrial applications and real-world modeling systems, for example in the context of image denoising, optimal control, neural network training, data mining, economics and computational chemistry and physics. The book covers both the theory and the numerical methods used in NSO and provide an overview of different problems arising in the field. It is organized into three parts: 1. convex and nonconvex analysis and the theory of NSO; 2. test problems and practical applications; 3. a guide to NSO software. The book is ideal for anyone teaching or attending NSO courses. As an accessible introduction to the field, it is also well suited as an independent learning guide for practitioners already familiar with the basics of optimization.

Adaptive Techniques for Dynamic Processor Optimization

Theory and Practice

Author: Alice Wang,Samuel Naffziger

Publisher: Springer Science & Business Media

ISBN: 9780387764726

Category: Technology & Engineering

Page: 304

View: 6633

This book is about various adaptive and dynamic techniques used to optimize processor power and performance. It is based on a very successful forum at ISSCC which focused on Adaptive Techniques. The book looks at the underlying process technology for adaptive designs and then examines different circuits, architecture and software that address the different aspects. The chapters are written by people both in academia and the industry to show the scope of alternative practices.

Homogenization and Structural Topology Optimization

Theory, Practice and Software

Author: Behrooz Hassani,Ernest Hinton

Publisher: Springer Science & Business Media

ISBN: 1447108914

Category: Mathematics

Page: 268

View: 2690

Structural topology optimization is a fast growing field that is finding numerous applications in automotive, aerospace and mechanical design processes. Homogenization is a mathematical theory with applications in several engineering problems that are governed by partial differential equations with rapidly oscillating coefficients Homogenization and Structural Topology Optimization brings the two concepts together and successfully bridges the previously overlooked gap between the mathematical theory and the practical implementation of the homogenization method. The book is presented in a unique self-teaching style that includes numerous illustrative examples, figures and detailed explanations of concepts. The text is divided into three parts which maintains the book's reader-friendly appeal.

Utility and Welfare Optimization

Theory and Practice in Electricity

Author: Chris Harris

Publisher: Springer

ISBN: 1137371005

Category: Political Science

Page: 261

View: 8655

Utility and Welfare Optimization in Electricity Market s lays out clear optimization strategies for understanding the economic foundations of regulatory supply measures, further cementing electricity's role as an asset class with fixed and variable costs.

Statistical Optimization for Geometric Computation

Theory and Practice

Author: Kenichi Kanatani

Publisher: Courier Corporation

ISBN: 0486443086

Category: Mathematics

Page: 509

View: 2951

This text for graduate students discusses the mathematical foundations of statistical inference for building three-dimensional models from image and sensor data that contain noise--a task involving autonomous robots guided by video cameras and sensors. The text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. The numerous mathematical prerequisites for developing the theories are explained systematically in separate chapters. These methods range from linear algebra, optimization, and geometry to a detailed statistical theory of geometric patterns, fitting estimates, and model selection. In addition, examples drawn from both synthetic and real data demonstrate the insufficiencies of conventional procedures and the improvements in accuracy that result from the use of optimal methods.

Linear and Integer Programming

Theory and Practice, Second Edition

Author: Gerard Sierksma

Publisher: CRC Press

ISBN: 9780824706739

Category: Mathematics

Page: 656

View: 8557

"Combines the theoretical and practical aspects of linear and integer programming. Provides practical case studies and techniques, including rounding-off, column-generation, game theory, multiobjective optimization, and goal programming, as well as real-world solutions to the transportation and transshipment problem, project scheduling, and decentralization."

Multi-Objective Optimization in Theory and Practice I: Classical Methods

Author: Andre A. Keller

Publisher: Bentham Science Publishers

ISBN: 1681085682

Category: Technology & Engineering

Page: 296

View: 6819

Multi-Objective Optimization in Theory and Practice is a traditional two-part approach to solving multi-objective optimization (MOO) problems namely the use of classical methods and evolutionary algorithms. This first book is devoted to classical methods including the extended simplex method by Zeleny and preference-based techniques. This part covers three main topics through nine chapters. The first topic focuses on the design of such MOO problems, their complexities including nonlinearities and uncertainties, and optimality theory. The second topic introduces the founding solving methods including the extended simplex method to linear MOO problems and weighting objective methods. The third topic deals with particular structures of MOO problems, such as mixed-integer programming, hierarchical programming, fuzzy logic programming, and bimatrix games. Multi-Objective Optimization in Theory and Practice is a user-friendly book with detailed, illustrated calculations, examples, test functions, and small-size applications in Mathematica® (among other mathematical packages) and from scholarly literature. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science, and mathematics degree programs.

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: 1201

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.

Optimization Theory and Methods

Nonlinear Programming

Author: Wenyu Sun,Ya-Xiang Yuan

Publisher: Springer Science & Business Media

ISBN: 0387249761

Category: Mathematics

Page: 688

View: 2731

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.

Nature-Inspired Computing and Optimization

Theory and Applications

Author: Srikanta Patnaik,Xin-She Yang,Kazumi Nakamatsu

Publisher: Springer

ISBN: 3319509209

Category: Computers

Page: 494

View: 1178

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.

Multi-Objective Optimization in Computational Intelligence: Theory and Practice

Theory and Practice

Author: Thu Bui, Lam

Publisher: IGI Global

ISBN: 1599045001

Category: Technology & Engineering

Page: 496

View: 4461

Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.

Foundations of Optimization

Author: Osman Güler

Publisher: Springer Science & Business Media

ISBN: 9780387684079

Category: Business & Economics

Page: 442

View: 7434

This book covers the fundamental principles of optimization in finite dimensions. It develops the necessary material in multivariable calculus both with coordinates and coordinate-free, so recent developments such as semidefinite programming can be dealt with.

Engineering Optimization

Theory and Practice

Author: Singiresu S. Rao,S. S. Rao

Publisher: John Wiley & Sons

ISBN: 0470183527

Category: Mathematics

Page: 813

View: 3528

Technology/Engineering/Mechanical Helps you move from theory to optimizing engineering systems in almost any industry Now in its Fourth Edition, Professor Singiresu Rao's acclaimed text Engineering Optimization enables readers to quickly master and apply all the important optimization methods in use today across a broad range of industries. Covering both the latest and classical optimization methods, the text starts off with the basics and then progressively builds to advanced principles and applications. This comprehensive text covers nonlinear, linear, geometric, dynamic, and stochastic programming techniques as well as more specialized methods such as multiobjective, genetic algorithms, simulated annealing, neural networks, particle swarm optimization, ant colony optimization, and fuzzy optimization. Each method is presented in clear, straightforward language, making even the more sophisticated techniques easy to grasp. Moreover, the author provides: Case examples that show how each method is applied to solve real-world problems across a variety of industries Review questions and problems at the end of each chapter to engage readers in applying their newfound skills and knowledge Examples that demonstrate the use of MATLAB® for the solution of different types of practical optimization problems References and bibliography at the end of each chapter for exploring topics in greater depth Answers to Review Questions available on the author's Web site to help readers to test their understanding of the basic concepts With its emphasis on problem-solving and applications, Engineering Optimization is ideal for upper-level undergraduates and graduate students in mechanical, civil, electrical, chemical, and aerospace engineering. In addition, the text helps practicing engineers in almost any industry design improved, more efficient systems at less cost.

Applied Optimization with MATLAB Programming

Author: P. Venkataraman

Publisher: John Wiley & Sons

ISBN: 047008488X

Category: Technology & Engineering

Page: 526

View: 5145

Over the last few decades, optimization techniques have been streamlined by the use of computers and artificial intelligence methods to analyze more variables (especially under non-linear, multivariable conditions) more quickly than ever before. This book covers all classical linear and nonlinear optimization techniques while focusing on the standard mathematical engine, MATLAB. As with the first edition, the author uses MATLAB in examples for running computer-based optimization problems. New coverage in this edition includes design optimization techniques such as Multidisciplinary Optimization, Explicit Solution for Boundary Value Problems, and Particle Swarm Optimization.

Applied Optimization

Formulation and Algorithms for Engineering Systems

Author: Ross Baldick

Publisher: Cambridge University Press

ISBN: 1107394082

Category: Technology & Engineering

Page: 786

View: 393

The starting point in the formulation of any numerical problem is to take an intuitive idea about the problem in question and to translate it into precise mathematical language. This book provides step-by-step descriptions of how to formulate numerical problems and develops techniques for solving them. A number of engineering case studies motivate the development of efficient algorithms that involve, in some cases, transformation of the problem from its initial formulation into a more tractable form. Five general problem classes are considered: linear systems of equations, non-linear systems of equations, unconstrained optimization, equality-constrained optimization and inequality-constrained optimization. The book contains many worked examples and homework exercises and is suitable for students of engineering or operations research taking courses in optimization. Supplementary material including solutions, lecture slides and appendices are available online at www.cambridge.org/9780521855648.