Reviews (2)

A great source of intuition.
Functional analysis and operator theory is a deep and useful subject, and is still an active area of research. Quantum theory, learning theory, and probability and statistics, are just a few of the areas that make heavy use of it, and it would be difficult to formulate ideas in these areas concisely if it were not for the results that are codified in functional analysis and operator theory.

This book, in spite of its age, can still be thought of as a definitive treatise in the subject, even though operator theory has grown tremendously since its date of publication. There are many fascinating results in this book it is one of the few treatises on mathematics that could in some sense be thought of as respecting a certain "oral tradition" in mathematics. Indeed, the "Notes and Remarks" sections at the end of each chapter give many insights on the origins of the subject and give those who crave for a more in-depth understanding of the subject. I studied this book in great detail when I was a sophomore undergraduate, having had the privelege of doing do under the tutelage of the late functional analyst Jeffrey Butz. The excitement he generated in the course, with his lucid lectures, makes the review of this book bring back fond memories. For lack of space, only the first seven chapters will be reviewed here.

In chapter 1, the authors give a quick review of the set theory, topology, and elementary analysis that will be needed for the reader to get through the book. Functional analysis can be thought of as a generalization of linear algebra to infinite dimensions, with analysis put in so as to be able to discuss convergence. Chapter 2 then discusses the three pillars of that functional analysis is dependent on: the principle of uniform boundedness, the interior mapping principle (and its immediate corollary the closed graph theorem), and the Hahn-Banach theorem. Uniform boundedness is presented in the context of what the authors call F-spaces, and is, as they point out, a principle of equi-continuity. The interior mapping principle guarantees that continuous linear mappings bring open sets to open sets, while the Hahn-Banach theorem ensures that there are in fact functionals in the dual of a Banach space. (Banach spaces are called "B-spaces" in this book, while the dual is called the "conjugate).

Then in chapter 3, the authors take the reader through a careful treatment of measure theory and the theory of integration. They do this first via the concept of finitely additive set functions taken over a field of subsets of a set (a Boolean algebra). These set functions are taken to be the measures, and are not assumed to be bounded, and more generally than is usually the case, are assumed to have values in a real or complex Banach space. Integration theory in this set-up begins, as expected, with simple functions, and Lebesgue spaces are defined as linear spaces of measurable functions. When the set functions are countably additive, one can extend them to a wider collection, called a sigma field. This brings up the Borel field, where the set is now a topological space, and is the smallest sigma-field containing the closed sets of this space. The authors illustrate how to extend the subsequent measures via an example: the construction of the famous Radon measure on an interval. Then a metric is introduced on the sigma-field of a measure space so that it is complete, and the authors then prove the Vitali-Hahn-Saks theorem. They also show how to represent the set functions in terms of integrable functions: the Radon-Nikodym theorem.

The "special spaces" of functional analysis are overviewed in chapter 4, such as the lp and Lp spaces so familiar in applications. The authors motivate the interest in these spaces in the context of solving eight problems, dealing with how to represent the dual space, the relation between convergence in a space and its dual, weak convergence of sequences, weak completeness of a space, reflexivity of a space, weak sequential compactness of subsets of a space, compactness of subsets in the metric topology, and the connection between convergence in a space and in the space it is dual to.

Chapter 5 is an introduction to the role that convexity plays in vector spaces, wherein the authors prove an analog of the Hahn-Banach theorem, showing to what extent linear functionals can be related to convex sets. When a topology is put on the vector space, the linear functionals can determine a a topology, which for Banach spaces is the famous weak topology. This chapter is very important in applications, such as learning theory and optimization theory, due to the notions of extremal points and fixed point theorems. The Krein-Milman theorem is proven, as well as the Kakutani fixed point theorem.

The authors finally get to operator theory in chapter 6, wherein they study bounded linear maps between Banach spaces. The strong, uniform, and weak topologies are introduced immediately, adjoints are defined, along with projections. Weakly compact operators, so important in the theory of integral equations are discussed, along with the compact operators, so ubiquitous now in operator theory. Concrete examples are given on the form that operators take in various kinds of spaces, like Lebesgue spaces.

Then the reader, in chapter 7, gets totally immersed in the eigenvalue problem in infinite dimensions: the spectral theory of operators. The finite dimensional case is reviewed first, and the spectral theory of compact operators, a generalization of the Fredholm theory of linear integral equations, is discussed in great detail. This subject has changed considerably since this book was published, now being done most concisely and transparently using the language of K-theory.

Great Book for Yesteryear!
There are people who love James Dean and Marilyn Monroe. This is the "Casablanca" - a great B/W movie for Functional Analysis. But, we are in a different age of big screen movie full of digital effects and sound effects. You are charged for a full price to watch an old master piece. My rating for this book is based on today's standard. Although, it is not fair for the book, but it is an unfortunate must for the reader! Of course, there are old books who stood firm in modern standard, e.g. Kolmogorov and Fermin's Introductory Real Analysis and Rudin's Functional Analysis. My rating for whether the school library should buy this book and its Part II and III is a definitely five stars!!! For beginners, my advise is don't read this intimidating thick book. ... Read more

Book Description

Linear programming finds the least expensive way to meet given needs with available resources. Its results are used in every area of engineering and commerce: agriculture, oil refining, banking, and air transport. Authors Kolman and Beck present the basic notions of linear programming and illustrate how they are used to solve important common problems. The software on the included disk leads students step-by-step through the calculations.
The Second Edition is completely revised and provides additional review material on linear algebra as well as complete coverage of elementary linear programming. Other topics covered include: the Duality Theorem; transportation problems; the assignment problem; and the maximal flow problem. New figures and exercises are provided and the authors have updated all computer applications.
The disk that comes with the book contains the student-oriented linear programming code SMPX, written by Professor Evar Nering of Arizona State University. The authors also recommend inexpensive linear programming software for personal computers.

* More review material on linear algebra
* Elementary linear programming covered more efficiently
* Presentation improved, especially for the duality theorem, transportation problems, the assignment problem, and the maximal flow problem
* New figures and exercises
* Computer applications updated
* Added disk with the student-oriented linear programming code SMPX, written by Professor Evar Nering of Arizona State University
* New guide to inexpensive linear programming software for personal computers ... Read more

Book Description

A pioneering look at the fundamental role of logic in optimization and constraint satisfaction
While recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to unifying the two fields. Logic-Based Methods for Optimization develops for the first time a comprehensive conceptual framework for integrating optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful as well as flexible modeling and solution techniques. Designed to be easily accessible to industry professionals and academics in both operations research and artificial intelligence, the book provides a wealth of examples as well as elegant techniques and modeling frameworks ready for implementation. Timely, original, and thought-provoking, Logic-Based Methods for Optimization:
* Demonstrates the advantages of combining the techniques in problem solving
* Offers tutorials in constraint satisfaction/constraint programming and logical inference
* Clearly explains such concepts as relaxation, cutting planes, nonserial dynamic programming, and Bender's decomposition
* Reviews the necessary technologies for software developers seeking to combine the two techniques
* Features extensive references to important computational studies
* And much more ... Read more

Book Description

This unique book explores the connections between the geometry of mappings and many important areas of modern mathematics such as Harmonic and non-linear Analysis, the theory of Partial Differential Equations, Conformal Geometry and Topology.Much of the book is new. It aims to provide students and researchers in many areas with a comprehensive and up to date account and an overview of the subject as a whole. ... Read more

Book Description

This volume provides an up-to-date overview of major advances, emerging trends, and projected industrial applications in the field of multidisciplinary optimization. It concentrates on the current status of the field, exposes commonalities, innovative, promising, and speculative methods. This book provides a view of today's multidisciplinary optimization environment through a balenced theoretical and practical treatment. The contributors are the foremost authorities in each area of specialisation. ... Read more

Reviews (1)

Excellent book
It is very good book for people who works in structural optimization. It has many nice examples. I will buy it for my library. ... Read more

Book Description

Fully describes optimization methods that are currently most valuable in solving real-life problems. Since optimization has applications in almost every branch of science and technology, the text emphasizes their practical aspects in conjunction with the heuristics useful in making them perform more reliably and efficiently. To this end, it presents comparative numerical studies to give readers a feel for possibile applications and to illustrate the problems in assessing evidence. Also provides theoretical background which provides insights into how methods are derived. This edition offers revised coverage of basic theory and standard techniques, with updated discussions of line search methods, Newton and quasi-Newton methods, and conjugate direction methods, as well as a comprehensive treatment of restricted step or trust region methods not commonly found in the literature. Also includes recent developments in hybrid methods for nonlinear least squares; an extended discussion of linear programming, with new methods for stable updating of LU factors; and a completely new section on network programming. Chapters include computer subroutines, worked examples, and study questions. ... Read more

Reviews (2)

Paperback reprint of 2nd Ed. from 1987
This is a good book from an award winning author and researcher in this subject. However, the 2000 publication date shown refers to the release of the paperback version. There is no new content since 1987 when the 2nd ed. was originally published in hardcover.

I prefer Dennis and Schnabel's _Numerical Methods for Unconstrained Optimization and Nonlinear Equations_ for Newton-derived methods in unconstrained optimization, but Fletcher's book has the added material on constrained optimization (Part 2) that makes it more complete if one wants a single reference that covers the gamut of optimization.

Help you know what's under the hood
This is a very well-written book. It achieved both mathematical clearness and simplicity. I especially like the first part, unconstrained optimization. On the one hand, unconstrained optimization is very widely used. On the other hand, there isn't much content in it. Yet, there aren't many books explaining this small area clearly. This book starts with describing the structures of all methods, which gives you a sort of bird's eye view. It then devotes one chapter to each of the 3 major families of optimization methods. Comparing with another popular book, Numerical Recipes, which is orgnized by individual algorithms, this book will cerntainly gives the reader better understanding of the essence of all the algorithms. And as the name says, it's about 'practial' methods. You'll have no problem to implement the algorithms in the book and there are also many working examples to help you see how an algorithm works and help verify the implementation. ... Read more

Reviews (1)

Good Examples BUT...a little too theoretical
I've used this book for a graduate course in Dynamic Programming. Having used many of Mr. Ross's books (undergraduate and graduate), I found this one lacks the detail and lucidity (particularly the end of chapter problems...I believe in "learning by doing"... i.e. solve lots of problems!) that I have come to know of his books (e.g. A First Course in Probability and Introduction to Probability Models). The bright spot of the book is its examples, which are interesting and fairly detailed. ... Read more

Book Description

This book serves as an introduction to queuing theory and provides a thorough treatment of tools like Markov processes, renewal theory, random walks, Levy processes, matrix-analytic methods and change of measure. It also treats in detail basic structures like GI/G/1 and GI/G/s queues, Markov-modulated models and queuing networks, and gives an introduction to areas such as storage, inventory, and insurance risk. Exercises are included and a survey of mathematical prerequisites is given in an appendixThis much updated and expanded second edition of the 1987 original contains an extended treatment of queuing networks and matrix-analytic methods as well as additional topics like Poisson's equation, the fundamental matrix, insensitivity, rare events and extreme values for regenerative processes, Palm theory, rate conservation, Levy processes, reflection, Skorokhod problems, Loynes' lemma, Siegmund duality, light traffic, heavy tails, the Ross conjecture and ordering, and finite buffer problems. Students and researchers in statistics, probability theory, operations research, and industrial engineering will find this book useful. ... Read more

Book Description

This book presents a variety of computational methods used to solve dynamic problems in economics and finance. It emphasizes practical numerical methods rather than mathematical proofs and focuses on techniques that apply directly to economic analyses. The examples are drawn from a wide range of subspecialties of economics and finance, with particular emphasis on problems in agricultural and resource economics, macroeconomics, and finance. The book also provides an extensive Web-site library of computer utilities and demonstration programs.

The book is divided into two parts. The first part develops basic numerical methods, including linear and nonlinear equation methods, complementarity methods, finite-dimensional optimization, numerical integration and differentiation, and function approximation. The second part presents methods for solving dynamic stochastic models in economics and finance, including dynamic programming, rational expectations, and arbitrage pricing models in discrete and continuous time. The book uses MATLAB to illustrate the algorithms and includes a utilities toolbox to help readers develop their own computational economics applications. ... Read more

Reviews (2)

Excellent for economists and financial analysts
This is one of the few books that covers the topics of numerical methods to solve finance and economics problems. It provides a large number of generic applications.

Readers that can use Matlab will especially benefit. If so, be sure to get the author's toolbox and see the errata on the author's page.

There are two other books that might be useful to those interested in this text: Dixit and Pindyck's Investment Under Uncertainty (1994), and Patrick Anderson's Business Economics and Finance (2004) [my book], which cites the Dixit and Miranda texts.

Readers should be prepared for some math, although it is much more accessible here than in most graduate texts in financial mathematics.

Fantastic book!
This book is a must for economists or financial engineers. I used the book in a course and refer to it often now that I work in the industry. The Matlab examples are also excellent. ... Read more

Book Description

Dynamic Optimization, by Arthur E. Bryson, takes an applied approach to its subject, offering many examples and solved problems that draw from aerospace, robotics, and mechanics. The abundance of thoroughly tested general algorithms and MATLAB codes provide the student with the practice necessary to master this inherently difficult subject, while the realistic engineering problems and examples keep the material interesting and relevant. ... Read more

Reviews (1)

Models mathematical
The behavior of the models mathematical in the stability of power systems ... Read more

Reviews (2)

Wright is always right
Excelent book, a must-have for everyone that has interest on the subject.

Excellent Book
Very accurate and detailed algorithm. Easy to be used in the real world application. ... Read more

Reviews (1)

A good reference source for convex optimization
Lectures on Convex Optimization is devoted to well structured
and efficiently solvable convex optimization problems, with
an emphasis on conic quadratic and semidefinite programming.
The authors begin with linear programming, and then progress
to conic programming. [I really enjoyed their description
of the transition from linear to general conic
programming!]. They then discuss two special conic
optimization problems namely second order cone programming,
and semidefinite programming. Numerous applications of conic
programming espcially in filter design, Lyapunov stability
analysis, and structural design are presented. The book concludes with
a discussion on the computational tractability of convex
programs, and primal dual interior point algorithms to
solving general conic optimization problems.

One can then take on the likes of Renegar's recent book
on interior point methods, and
Nesterov and Nemirovski's seminal treatise on the general
theory of interior point methods in convex optimization,
at a more advanced level.

My only minor comments are :-
(a) The organization of the book as a series of 6 lectures
is misleading, since there is quite a lot of material
covered in each lecture.
(b) The book has a very short [almost
nonexistent] bibliography.

All in all, a good workout and an encyclopedic source for
anyone interested in theory and applications of convex
optimization. Highly recommended!. ... Read more

Book Description

A path-breaking account of Markov decision processes-theory and computation

This book's clear presentation of theory, numerous chapter-end problems, and development of a unified method for the computation of optimal policies in both discrete and continuous time make it an excellent course text for graduate students and advanced undergraduates. Its comprehensive coverage of important recent advances in stochastic dynamic programming makes it a valuable working resource for operations research professionals, management scientists, engineers, and others.

Stochastic Dynamic Programming and the Control of Queueing Systems presents the theory of optimization under the finite horizon, infinite horizon discounted, and average cost criteria. It then shows how optimal rules of operation (policies) for each criterion may be numerically determined. A great wealth of examples from the application area of the control of queueing systems is presented. Nine numerical programs for the computation of optimal policies are fully explicated.

The Pascal source code for the programs is available for viewing and downloading on the Wiley Web site at www.wiley.com/products/subject/mathematics. The site contains a link to the author's own Web site and is also a place where readers may discuss developments on the programs or other aspects of the material. The source files are also available via ftp at ftp://ftp.wiley.com/public/sci_tech_med/stochastic

Stochastic Dynamic Programming and the Control of Queueing Systems features:
* Path-breaking advances in Markov decision process techniques, brought together for the first time in book form
* A theorem/proof format (proofs may be omitted without loss of continuity)
* Development of a unified method for the computation of optimal rules of system operation
* Numerous examples drawn mainly from the control of queueing systems
* Detailed discussions of nine numerical programs
* Helpful chapter-end problems
* Appendices with complete treatment of background material ... Read more

Reviews (1)

Good book for stochastic DP
I have read other books of "Stochastic Processes" by Ross,"Introduction to Stochastic Processes" by Stone.Certainly this book is a good one to span you knowledge.Largely it covers Queueing Systems in the later part,but a really really nice introduction to the terms necessary.

If you are familiar to these terms of Stochastic Processes i would highly recommend it.If not so,even then first 4 chapters talk abt finite and infinte horizon optimization,introduces you to other necessary terms.And then just go go go.

The FTP site of the publisher lets you download the pascal programmes so that u can run them and test them for your own purpose.

The problems at the end of the each chapter is the best way to test your learnt knowledge,they are little bit mind teasers(I felt so).

OverAll a good book for those who are comfortable with LOTS of equations and Probablity. ... Read more

Book Description

Synchronization processes bring about dynamical order and lead to spontaneous development of structural organization in complex systems of various origins, from chemical oscillators and biological cells to human societies and the brain. This book provides a review and a detailed theoretical analysis of synchronization phenomena in complex systems with different architectures, composed of elements with periodic or chaotic individual dynamics. Special attention is paid to statistical concepts, such as nonequilibrium phase transitions, order parameters and dynamical glasses. ... Read more

Book Description

The study of nonlinear dynamical systems has advanced tremendously in the last 15 years, making a big impact on science and technology. This book provides all the techniques and methods used in nonlinear dynamics. The concepts and underlying mathematics are discussed in detail.

The numerical and symbolic methods are implemented in C++, SymbolicC++ and Java. Object-oriented techniques are also applied. The book contains more than 100 ready-to-run programs.

The text has also been designed for a one-year course at both the junior and senior levels in nonlinear dynamics. The topics discussed in the book are part of e-learning and distance learning courses conducted by the International School for Scientific Computing. ... Read more

Reviews (2)

Helpful in some sections
The topics covered in this book are all important from the standpoint of applications in physics, engineering, computer science, financial engineering, and computational biology. It is written for the person just getting started in these topics, and the author does a fairly good job of discussing them. Readers should not expect, and they will not get, in-depth discussions on these topics, as this would swell the book to 10 times the size. They will however get preparation for moving on to more advanced and complete treatments.

Nonlinear and chaotic maps are considered in chapter 1, with elementary definitions given and six different examples of maps discussed. In discussing the calculation of numerical trajectories of maps, the author deals with the problem of large initial values for the maps and how to implement these in SymbolicC++ and Java. He also shows how to write/read data to a file using C, C++, and JAVA. The exception handling capability of JAVA comes out nicely, but no performance comparison between the three languages for simulating the maps is given by the author. The language REDUCE is used to discuss the stability of the fixed points of the logistic equation, but the code would be useless to the reader who did not have REDUCE since some of the function calls are hidden from the reader. Useful programs are given for calculating the Lyapunov and autocorrelation functions. In addition, C++ programs are given for evaluating the correlation integral for the Henon map. The programs he develops in this chapter can serve as a quick benchmark for one's own programs that calculate the same quantities.

In chapter 2, the author discusses methods for studying time series, including the Lyapunov and Hurst exponents. These two quantities are of enormous importance in the study of dynamical systems, financial data, and network performance. The C++ program that the author gives for calculating the Hurst exponent will not work for arbitrary time intervals. This is followed in the next chapter by a consideration of autonomous systems of ordinary differential equations. The classification of fixed points is considered, and the important concept of a homoclinic orbit. The author gives a nice JAVA program that finds the homoclinic orbit of an anharmonic differential equation using the Lie series technique. The phase portrait of the Van der Pol oscillator is calculated using the Runge-Kutta technique in a C++ program, along with the Lotka-Volterra system from mathematical biology.

Hamiltonian mechanics is discussed in chapter 4, with the important Henon-Heiles model from astrophysics is discussed and JAVA programs given for studying its behavior using the Poincare section technique. Newcomers to this technique will appreciate seeing it done here explicitly.Integrability of Hamiltonian systems using the Lax representation and Floquet theory are also treated, but only at a very rudimentary level. Dissipation is included in the next chapter, and the author discusses the classification of fixed points according to their stability. Lyapunov exponents are again brought into the picture, and the phenomenon of hyperchaos is discussed. Some bifurcation theory is introduced with an example of the Hopf bifurcation. Chapter 6 studies nonlinear driven systems, with the Duffing oscillator treated, and the author gives a useful program for calculating the autocorrelation function of this system. The controlling of chaos with feedback and non-feedback controls is the subject of the next chapter, mostly in the context of difference maps. Fractals finally get introduced in chapter 8, with iterated function systems defined but proofs of their properties omitted. The author gives programs for calculating various popular fractals, such as the dragon, Sierpinski gasket, Koch curve, the Mandelbrot set, and the Julia set. The main disappointment in this chapter is that the author does not give programs for calculating the Hausdorff dimension or capacity, quantities that are notoriously difficult to get a meaningful computational handle on.

The author switches gears in the next chapter and discusses cellular automata, which have recently made a comeback, especially in research on quantum computation. The discussion is too brief however, and does not allow the reader to gain an appreciation of the properties of these important objects. Chapter 10 gives a brief overview of some techniques for solving differential equations, such as the Euler method and the Lie series technique. The latter is not commonly treated in beginning books so its inclusion here is helpful. Symplectic integration is also discussed briefly, but the author does not discuss how to check the integrators using backward integration, which is commonly used in conservative systems modeled by symplectic maps.

Chapter 11, covering neural networks, is the most well-written in the book, and the newcomer to the field will get a fairly decent introduction to the subject. The supplied programs serve to illustrate some of the important concepts in neural networks, such as the Hopfield model, the Kohonen network, the perceptron learning algorithm, and the back-propagation algorithm.

Chapter 12 is an introduction to genetic algorithms, and I find this one particularly nice also, as it does give a rudimentary introduction to what evolutionary algorithms are all about, and gives some elementary genetic programs that find the maximum of one- and two-dimensional maps. He also discusses simulated annealing, and gives a useful program that allows the reader to see clearly how this technique works.

The last chapter covers fuzzy sets and fuzzy logic, which has also taken on importance in recent years, especially in data mining and financial engineering. The programs given to illustrate the concepts are particularly interesting from the standpoint of coding in C++, as the author uses friend functions and operating overloading in some of them. The reader gets a good overview of fuzzy reasoning and fuzzy rule-based systems.

Useful information, poor presentation
The information was useful & approprate to the topic.I'd rank it as an average quality refence but a very poor text book.

The text is poorly written.The code is simple and easy to understand, but not very objectoriented.There is not enough explanation of the code.The code is notelectronically available.

The treatment was very mathematical but lackingin explanation & application examples.There were plenty ofdeffinitions, but not enough examples. ... Read more

Book Description

This text presents linear and nonlinear programming in an integrated setting and serves as a complete and unified introduction to applications, theory, and algorithms. ... Read more

Reviews (3)

nothing special
the fact that none of the exercises have solutions is bothersome. i also had difficulty determining which ideas/equations have more emphasis than others. this book shouldn't be used as an introductory course due to its mediocre-at-best layout.

There are better books...
I found this book to be not so good for non linear programming. The notation is confusing and the discussion of subject itself is not organised. I prefer other books like the book by Bertsekas. I followed Bazaara's book for linear programming and hence I dont know about this book's linear programming.

clear
In my opininon it is more clear than the other examples of this category. But a deficiency for this book is there is no solutions to the problems as exercises. ... Read more

Book Description

This text provides a first course in numerical methods and programming taught through the medium of MATLAB. It is designed to give readers their first exposure to any kind of programming. The first three chapters introduce readers to the power of MATLAB without overwhelming them with its advanced features; the text then covers all the elementary material associated with numerical methods, and helps students develop skills in algorithm design. Examples of code are provided to debug, hence accentuating the need for precision, and developing readers’ skills in finding errors in their own work. At the end of each chapter, tasks are provided to reinforce the ideas introduced, with full solutions at the back of the book. A glossary of terms is provided, with each term supported by an example of the syntaxes commonly encountered.

Aimed at first and second year undergraduates in mathematics and engineering, this book will also be invaluable for engineers who need to use MATLAB in their work environment.

Book Description

Today’s need-to-know optimization techniques, at your fingertips

The use of optimization methods is familiar territory to academicians and researchers. Yet, in today’s world of deregulated electricity markets, it’s just as important for electric power professionals to have a solid grasp of these increasingly relied upon techniques.

Making those techniques readily accessible is the hallmark of Optimization Principles: Practical Applications to the Operation and Markets of the Electric Power Industry.

With deregulation, market rules and economic principles dictate that commodities be priced at the marginal value of their production. As a result, it’s necessary to work with ever-more-sophisticated algorithms using optimization techniques–either for the optimal dispatch of the system itself, or for pricing commodities and the settlement of markets. Succeeding in this new environment takes a good understanding of methods that involve linear and nonlinear optimization, including optimal power flow, locational marginal prices for energy, and the auction of hedging instruments.

In its comprehensive, skill-building overview of optimization techniques, Optimization Principles puts you on the same footing with algorithm-savvy software developers. Starting with a helpful look at matrix algebra fundamentals, this just-in-time reference covers:

• Deregulated electricity markets: terminology and acronyms
• Solution of equations, inequalities, and linear programs
• Unconstrained and constrained nonlinear optimization
• Applications to practical problems addressing system dispatch, market design, and material procurement
• And related topics

As an aid to the uninitiated, appendices provide a brief description of basic principles of electricity, and the development of network equations.

Optimization Principles allows you to learn optimization methods at your own pace using Microsoft Excel or MATLAB software, and it includes an FTP web site with downloadable Excel spreadsheets and problems. After mastering these practical applications, you can then refer to chapters that highlight the theoretical background of the algorithms and resulting solutions. The book also includes a Web site with downloadable files of all example problems and solved problems.

Ideal for engineers, other electric power professionals, and advanced engineering students, Optimization Principles demystifies the electric power industry under deregulation–and delivers a complete, learn-as-you-go tutorial of optimization techniques that no other resource can match. ... Read more