Scientific Computing

Book Description

Heath 2/e, presents a broad overview of numerical methods for solving all the major problems in scientific computing, including linear and nonlinear equations, least squares, eigenvalues, optimization, interpolation, integration, ordinary and partial differential equations, fast Fourier transforms, and random number generators. The treatment is comprehensive yet concise, software-oriented yet compatible with a variety of software packages and programming languages. The book features more than 160 examples, 500 review questions, 240 exercises, and 200 computer problems. Changes for the second edition include: expanded motivational discussions and examples; formal statements of all major algorithms; expanded discussions of existence, uniqueness, and conditioning for each type of problem so that students can recognize "good" and "bad" problem formulations and understand the corresponding quality of results produced; and expanded coverage of several topics, particularly eigenvalues and constrained optimization. The book contains a wealth of material and can be used in a variety of one- or two-term courses in computer science, mathematics, or engineering. Its comprehensiveness and modern perspective, as well as the software pointers provided, also make it a highly useful reference for practicing professionals who need to solve computational problems.

Customer Reviews:

very nice conceptual overview.......2006-07-22

Wow, people seem to be really split on this book. I had Mike Heath for numerical analysis/scientific computing and he was an excellent instructor, one of the best lecturers I've ever had. (As a consequence, I have a hard time separating the book and the class, so judge accordingly.) The book is based on his lecture notes, though he added some material and didn't cover every topic in the book. Just reading the book is useful to give you an overview of the point behind different methods. The goal of the class for which this book was written is actually quite conceptual. It was to give scientists (that's me: a stats researcher who makes heavy use of numerical computation) and CS people in areas other than scientific computing a leg up. It was only a first class for people in scientific computing, the rough equivalent of intro Physics or intro Probability/Stats for people in those respective majors. However, you *won't* be prepared to "roll your own" from this book. In fact, at the beginning of the semester Heath was very careful to note that if you have the opportunity to use a library function for most numerical programming, you are nuts to roll your own. Why? Numerical algorithms are usually extremely complicated and the authors of the code often spend years developing careful expertise on them. Frequently the formulas used to elucidate a given method are NOT the ones used to implement it. You need error traps, tricks to handle ill-scaling and other special cases, etc. These are things that someone who has a one-semester, superficial understanding of a topic simply won't have. So consider the book on the goals it set: it is an overview of a field. If you want to learn more about any one topic, you have to dig deeper and consult references and other works, but this is a good place to start. For this, the book serves admirably.

Not for the practitioner.......2005-11-17

If you are interested in Scientific computing from the viewpoint of the end user that is the guy who uses the method to solve practical engineering problems then this book is lacking.

Not enough methods in this book to constitute an introductory survey of the field. Every chapter gets heavy dose mathematical treatment, apparently Heath loves his math but for the rest of us it doesnt translate into know-how. Know how to solve equations using computational techniques. Very few derivations to back his mathematical swagger, very few examples (if any) and fewer numerical schemes to solve problems. Many of the chapters receive cursory treatment such as PDE's get about 70 pages of print. Far too little to do anyone any good.

He does talk about interesting issues such as conditioning and error analysis and computer precision and memory issues but it is done from such a superficial viewpoint that one cannot use anything to improve ones code. Not recommended if you want to learn numerical methods even if you have an excellent professor to learn from. His chapter on FFT's was even more abstruse and there was hardly any methods with which to solve PDE's.

I had this for a graduate course in Numerical Methods but ended up using Hoffman's excellent book on Numerical Methods.

Trash.......2005-10-14

If you want to have a solid understanding of numerical computation, this book is definitely the last choice. Many theorems are given without any proof or even intuitions behind them in this book. Even when a proof is provided, it's often far from rigorous. The organization of chapters is the worst I have ever seen, revelant materials are scattered over several different locations rather than put together. Take the SVD for example, it is mentioned in the end of chapter 3, but reappears in chapter 4, which is very confusing. If you are new to this area, please don't read this book. It gives you many many facts without explanations, which I think is not a good way to learn new things. David S. Watkins' Fundamentals of Matrix Computations is a lot better and easier to understand. It also emcompasses many detailed treatments of various theorems. If you have bought Heath's book, don't be sad, at least it can serve as a coaster.

Excellent Introduction, Sparse on Details.......2004-11-20

While sparse on the details of many of the algorithms and theorems mentioned, as an introduction it covers a broad range of material-enough for two semesters of study. The writing is lucid, and when a proof of a theorem is given, it is easy to follow and explained in english afterward. Rationale is given for everything, which is a great benefit to a student not familiar with the nuances of sophisticated linear algebra.

A Good Introductory Survey.......2002-11-05

This book excels at presenting a reader with little to no knowledge in computer science and a mild mathematical background (knowledge of differential equations as a prerequisite) with the fundamental concepts regarding scientific computing. The presentation of pseudo-code algorithms helps smooth the transition from analytical (pencil and paper) thinking to numerical thinking. The algorithms are presented in a manner such tha anyone with access to dozens of possible environments can apply them, though they are by no means complete, thus requiring some thought into the processes. The material covered is 110% of what an engineer will want to know, 90% of what an applied mathematician will want to know, and 45% of what a numerical analyist will want to know. In all, a great book to begin a foray into numerical computing.

Average customer rating:

Kind of old stuffs
Optimization Mini-Library
It's not the technique, it's the logic behind it
improve your problem solving ability
get this book!, read it!, understand it! :)

How to Solve It: Modern Heuristics
Zbigniew Michalewicz , and David B. Fogel
Manufacturer: Springer
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ASIN: 3540224947

Book Description

This book is the only source that provides comprehensive, current, and correct information on problem solving using modern heuristics. It covers classic methods of optimization, including dynamic programming, the simplex method, and gradient techniques, as well as recent innovations such as simulated annealing, tabu search, and evolutionary computation. Integrated into the discourse is a series of problems and puzzles to challenge the reader. The book is written in a lively, engaging style and is intended for students and practitioners alike. Anyone who reads and understands the material in the book will be armed with the most powerful problem solving tools currently known.

This second edition contains two new chapters, one on coevolutionary systems and one on multicriterial decision-making. Also some new puzzles are added and various subchapters are revised.

Customer Reviews:

Kind of old stuffs.......2007-09-23

The material is alright but it is just kind of old. I can not tell from the original description otherwise, I will
not have bought it.

Optimization Mini-Library.......2007-02-20

This is the best book I have in my optimization library. It is excellent for students and teachers as well. It introduces you to optimization using a simple language, practical examples explained in a very didactical manner. It surveys optimization techniques and categorizes it in a very well-arranged and simplified format. You wouldn't have to read tens of pages with unsightly symbols, messed with subscripts and superscripts to understand a single optimization technique.
It also brings an uplifting introduction to the concept of problem solving. I highly recommend this book to Optimization and Mathematics students and teachers.
Read the book, once you are done, look at the table of contents and give a five minutes lecture on each single title and subtitle, which is what you will be capable of doing at the end.

It's not the technique, it's the logic behind it.......2006-07-24

Most evolutionary computation or math books deal with the techniques of solving problems. This book teachs you how to think of a solution for the problem you face, and not what problems are appropriate for the technique in hand.

The logic is that when you do a craft work, you do pick the appropriate tool from your tools box, but you don't grasp a tool and then find a job to go with it, which is the case when you can only handle this tool.

improve your problem solving ability.......2006-02-20

The authors have updated their successful first edition, though the latter, printed in 99, was scarcely obsolete. A heuristic can be basically a rule of thumb, dressed up in fancier language. What the authors intend is for you to develop an intuition about when to use modern algorithms. Where is almost every case, these are actually implemented on a computer; a reflection of the cheap availability of computing power to most readers.

The book is a good complement to various standard algorithm texts, like those by Sedgewick, Aho and Knuth. You can consider this book as standing a level above those. [Though Knuth's books also do an excellent job of suggesting when to use or modify algorithms. ]

The level of discussion here is not of a strict, heavy mathematical approach. It can be read as informal guidelines, that discuss the gist of such ideas as simulated annealing and evolutionary methods. There is a wide range of example problems, to motivate you in understanding what might be used to solve them.

get this book!, read it!, understand it! :).......2006-01-01

i have not finished reading this book, but it's 'worth it' if only for the first two chapters! :) anyone interested in dynamical systems (control aspects), general problem solving, AI, and human thinking should read and understand this book! :) work the problems! :) think! enjoy! :)

Network Flows: Theory, Algorithms, and Applications

Average customer rating:

the best network flow book for computer scientists
Good Introductory Book
Great book for Network Theory and Application
Great book for Network Theory and Application
PLEASE, write a corrected edition!

Network Flows: Theory, Algorithms, and Applications
Ravindra K. Ahuja , Thomas L. Magnanti , and James B. Orlin
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

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ASIN: 013617549X

Book Description

Bringing together the classic and the contemporary aspects of the field, this comprehensive introduction to network flows provides an integrative view of theory, algorithms, and applications. It offers in-depth and self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including a description of new and novel polynomial-time algorithms for these core models. For professionals working with network flows, optimization, and network programming.

Customer Reviews:

the best network flow book for computer scientists.......2004-12-18

I've been using this book as the primary text for my class in
"Network Flow Programming" (senior & graduate level) at the
University of Tennessee for about 10 years. Prior to that time
I had used Jensen & Barnes' Network Flow Programming (now long out
of print). The code in Jensen & Barnes is in FORTRAN (not so fun
or useful for CS majors) and the intended audience seemed to be OR.
Ahuja's code is pascal pseudo-code for the most part, which usually
translates easily into the C language that most of our students
use.

For CS students, there is excellent use of algorithm analysis
(big-O) throughout the book, and there are long discussions
about different approaches and algorithms and the complexity of
each. There is a lot of mathematical notation, but my students
have never had to worry about PDEs and the like here. Any good
advanced CS student (graduate or undergraduate) will find the
book very worthwhile. In my course the students must implement
min-cost spanning trees, shortest paths, critical path/PERT
networks (not in Ahuja), max flow, and min-cost flow. I would
also recommend (for CS majors) Tarjan's excellent (and
succinct) Data Structures and Network Algorithms.

Good Introductory Book .......2004-12-13

This is a good introductory book. I particularly liked the applications of the problems, introduced in the book. The main negative point that I could mention is, the redundant explanations and discussions you might see in different chapters. I would say the volume of the book could have been reduced by some 15%-20%, if the authors had chosen to be more concise.
The book, Combinatorial Optimization by William J. Cook, et al, is an alternative. It covers a whole lot of topics and is just too succinct, a little more elaboration would have been appreciated !

Great book for Network Theory and Application.......2003-09-25

This book contains a lot of great algorithms for network flow theory and it also contains many of the great applications, which are very useful in practice. This book is very completed. Personally, I learn a lot of new things about Multi commodity Flow, which are the use of Lagrangian Relaxation, Column generation, Resource allocation techniques for solving multi commodity flow. There are also the good chapters in Convex cost flow and Generalized Flow and good appendix in complexity. Beside this book is very easy to read and understand. It is a great idea to have if you are in OR or IE major. :)

Great book for Network Theory and Application.......2002-08-01

PLEASE, write a corrected edition!.......2002-02-28

First of all, I am not surprised that the book
got so many good reviews: at first look, it is truly
impressive, and it is clearly a work of love. I was
looking forward to teaching from it.

It is quite clear from the reviews though, that the
reviewers have not **used** it for teaching; they may
have browsed it at most.

The first disappointments came very soon in the course I
taught. The biggest flaw of the book is the really bad style
in which the proofs are written. They manage to be seemingly
overflowing with explanation, and at the same time difficult
to understand. They gloss over many details: if the teacher
tries to skip these, an alert student could easily make
him/her look pretty silly.

One case in point is the proof of the label correcting
algorithm's correctness starting on page 136. I knew this
material from before, so I thought preparing class from
here would be a breeze. I was wrong: after going back to
my notes, and breaking up the mess into several simple
claims did I manage to make notes from which I could teach.
Whoever missed the class was helpless, when they looked
for explanation in the book.

I only remark, that all classes that I taught from this book
were at some of the top 10 OR depts at the US... so this is
hardly the students' fault.

Many exercises are wrong as well, and although the authors
claim that they will try to fix the mistakes, they hardly ever
reply to reader's comments, as some of my fellow professors
told me.

I can only compare the style of the exposition to the
later written Combinatorial Optimization book by
Cunningham et. al. There is a WORLD of difference.
One can try to look up for instance, the proof
for the label correcting algorithm: the proof in the
Ahuja et. al book is practically creaking at the joints,
while in Cunningham et. al. it flows lucidly.
I suspect that the authors of the latter book wrote it, since
they were unhappy with this one; one can hardly be surprised.

On the positive side, the plethora of applications presented
is truly amazing, and the exercises (when correct) are excellent.

To sum it up: A good book, which could have become a great one,
but have not; one which is very useful, but at the
same time very hard to use... I think the community would thank
the authors for a second, revised edition, that would fix
all the mistakes, and all those terrible proofs.

A final word: this text received the prestigious Lanchester
prize. One may surmise that giving prizes to a textbook
would be best done maybe after 5 years, after a book proved
its worth in actual teaching in the trenches,
so to speak, and NOT based on the first impression that the
jury gets.

Average customer rating:

a wide variety of topics

Very nice introduction

Short and Sweet

Much needed desktop reference for anyone working with algorithms, networking protocols, optimization

Only for graduate level - very good

Approximation Algorithms
Vijay V. Vazirani
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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Randomized Algorithms

Combinatorial Optimization: Algorithms and Complexity

Computers and Intractability: A Guide to the Theory of NP-Completeness (Series of Books in the Mathematical Sciences)

Approximation Algorithms for NP-Hard Problems

Probability and Computing: Randomized Algorithms and Probabilistic Analysis

Accessories:

Parallel and Distributed Processing and Applications: 4th International Symposium, ISPA 2006, Sorrento, Italy, December 4-6, 2006, Proceedings (Lecture Notes in Computer Science)

Algorithms and Computation: 17th International Symposium, ISAAC 2006, Kolkata, India, December 18-20, 2006, Proceedings (Lecture Notes in Computer Science)

ASIN: 3540653678

Book Description

This book covers the dominant theoretical approaches to the approximate solution of hard combinatorial optimization and enumeration problems. It contains elegant combinatorial theory, useful and interesting algorithms, and deep results about the intrinsic complexity of combinatorial problems. Its clarity of exposition and excellent selection of exercises will make it accessible and appealing to all those with a taste for mathematics and algorithms.

Richard Karp,University Professor, University of California at Berkeley

Following the development of basic combinatorial optimization techniques in the 1960s and 1970s, a main open question was to develop a theory of approximation algorithms. In the 1990s, parallel developments in techniques for designing approximation algorithms as well as methods for proving hardness of approximation results have led to a beautiful theory. The need to solve truly large instances of computationally hard problems, such as those arising from the Internet or the human genome project, has also increased interest in this theory. The field is currently very active, with the toolbox of approximation algorithm design techniques getting always richer.

It is a pleasure to recommend Vijay Vazirani's well-written and comprehensive book on this important and timely topic. I am sure the reader will find it most useful both as an introduction to approximability as well as a reference to the many aspects of approximation algorithms.

László Lovász, Senior Researcher, Microsoft Research

Customer Reviews:

a wide variety of topics.......2006-11-07

Vazirani's book seems well suited for a computer science researcher who has had a rigorous background in pure maths. The level of difficulty can be quite advanced. Also, it is not the sort of book that gives algorithm examples in an actual programming language. Not that this should be a handicap to a skilled reader. The algorithms are usually described in high level pseudocode. You have to manually instantiate these in the language of your preference.

The 30 chapters span a wide variety of computational topics. Some are simpler than others to understand. Like the chapter on finding the shortest vector from the integer lattice made from a set of linearly independent vectors. That requires only a year or so of introductory linear algebra.

There are exercises for each chapter. Some exercises are formidable. Essentially like little research problems in their own right. Another plus for the book.

Very nice introduction.......2006-05-20

This is a quite nice book by an author who is well-known in the field. The book is not thematic, instead it presents certain problems in each chapter along with the main approximation algorithms and correctness proofs. Yet, each new concept is well introduced with the problems. For instance, the author presents LP-based techniques on the same problem (set cover) in the second part of the book. This makes it quite easy to compare and understand different techniques. The last part of the book is a little bit advanced compared to the first two parts which uses combinatorial or LP-based analysis of the algorithms. The presentation of the PCP theorem- arguably the deepest theorem of computer science- and its consequences are also in the last part.

A warning though: The book is quite terse at times, which enforces a dense reading. This may not be suitable for an undergradute study. My only complaint is that the PCP theorem might well be introduced with a little more intution.

Overall, I rate this book as excellent. If you are interested in algorithms, you should definitely buy it. Also, buy the "Complexity and Approximation" by Ausiello, Crescenzi and others. They provide a more comprehensive and thematic treatment. It also has an excellent bibliography and list of NP-hard problems. These two will make a great couple. The book edited by Hochbaum (Approximation Algorithms for NP-hard problems) on the other hand presents detailed information on the algorithms.

Short and Sweet.......2006-03-13

This is a fanastic topics book in approximation algorithms. The problems and proofs are challenging and concise, but written in a very accessible manner. It is a great reference book, and also a convenient place to grab a lecture from if you need something to fill our a course. I have found it extremely useful, and even fun to read. I highly reccomend it for any person interested in theoretical computer science.

Much needed desktop reference for anyone working with algorithms, networking protocols, optimization.......2006-03-09

I have been looking for books related to solving NP-complete and NP-hard problems approximately. There is another book by Hochbaum and I have that too. Unfortunately, that book is more of a research oriented book as it is written by several researchers. It's like reading several research papers within two hard covers. This means that one needs to have a sort of intermediate level of experience with approximation algorithms.

For a beginner, one would expect a book that starts from ground-up and that has been written as a textbook rather than as a set of research papers. The book by Dr. Vazirani, is the only book that is written by one author with a step-by-step evolution of concepts and ideas related to approximation algorithms.

Only for graduate level - very good.......2005-11-22

Very good, it is easy to read the book if you have a good level
of knowledge and the experience to think some details in the
proofs of the theorems.
I think it is a very good book for a graduate student.

ADTs, Data Structures, and Problem Solving with C++ (2nd Edition) (Alan R. Apt Books)

Average customer rating:

Great Introductory Book
Crisp as New.
Great book
Data Structures with C++ and STL not only for C programmers

ADTs, Data Structures, and Problem Solving with C++ (2nd Edition) (Alan R. Apt Books)
Larry R. Nyhoff
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

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ASIN: 0131409093

Customer Reviews:

Great Introductory Book.......2005-10-30

I actually feel that this book is a mixed bag. On one hand, the concepts are intuitively presented and are easy to understand. On the other hand, the book doesn't delve too much into technical details, which may or may not be a godsend to various students. Personally, I'd rather use the Drozdek Data Structures text, since it goes into much more detail into analysis and logic behind choosing various data structures and algorithms in order to implement an ADT.

Anyway, it's still a great textbook for an introductory course in data structures. Just be sure to get another textbook on the same material down the road if you want to get a more detailed understanding of the concepts presented.

Crisp as New........2005-09-17

The book shouldn't be called Used, its was Crisp as New, and exactly what you wanna expect at the start of a new class, having a colourful mak free book in your hands.

Great book.......2005-06-18

The coverage of C++ and data structures looks pretty good. There are lots of programming examples, and the book is written very well. I'm recommending it for our 2nd year course in data structures and C++. Our students know Java, but not C++, so it's been a challenge finding a data structures book that packages a semi-introductory version of C++ with a standard course in data structures. This book appears to be the best suited out of about 5-10 books that I've reviewed for this course.

Data Structures with C++ and STL not only for C programmers.......2004-09-28

I am teaching the second programming / first data structure course in the department of electrical and computer engineering. I have used the first edition of this book several times, and as of fall of 2004 I am into the third of semester of using this second edition as a mandatory text.

This book is very good for students who already know how to program in C, C++ or Java. The first C or C++ course does not have to cover introduction to OOP though. My students learn C part of C++ in the first programming course. This book covers object oriented programming part of C++, and introduces/reintroduces pointers, file IO with streams, and C++ strings (good for former Java programmers). Then it follows into data structures. It starts with its own definitions of dynamic array that grows, and a simple linked list as basic data containers. Then it focuses on organizing access to data with stack and queue, and then migrates to the standard template library (STL). Everything is kept on the undergraduate student level. All other STL books I know assume that you are already an expert in programming or at lest for students after two programming courses, and are too difficult for average non-CS students.

I originally rated the first edition with four-stars only because it introduced pointers very late, out of the proper sequence and added the fifth star for the unique blend of introduction to OOP C++ and data structures, and STL. However, this edition is free from this inconvenience and it also makes C++ and data structures course accessible to former Java programmers. It gets true five stars from me this time.

Innovation Algorithm:TRIZ, systematic innovation and technical creativity

Average customer rating:

Revolutionary in Approach.
The Bible of TRIZ

Innovation Algorithm:TRIZ, systematic innovation and technical creativity
Genrich Altshuller
Manufacturer: Technical Innovation Ctr
ProductGroup: Book
Binding: Paperback

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ASIN: 0964074044

Book Description

A milestone in the development of the Theory of Inventive Problem Solving (TRIZ), this book is the result of over twenty years of research and analysis. Altshuller details TRIZ's problem solving algorythm (ARIZ) that can produce innovation of the highest order. Saturated with profound thoughts, insights, and examples, this book is regarded by many as Altshuller's magnum opus, his handbook for a creative and technological revolution.

Customer Reviews:

Revolutionary in Approach........2001-07-31

This is one of the truly great and original contributions to the field of creativity. Altshuller's approach shows the inadequacy of many of the existing systems of creative problem solving. I loved everything about this book, from his analysis of problem spaces, thinking backwards from the solution to it's systematic emphasis on dealing with contradictions was first rate and that's just some of the topics. My only problem with the book was that it was geared towards engineering problems and the examples while intriguing were a bit mysterious to this non-engineer. However, with a bit of thinking and some collateral resources, I think this approach can be used to solve any problem.

The Bible of TRIZ.......2000-04-08

I have read all available books on TRIZ and found no better than this. As comprehensive and deep as "Creativity as an exact science", it is more clear, systematic, and legible.

Approximation Algorithms for NP-Hard Problems

Average customer rating:

A good survey on approximation algorithms

Approximation Algorithms for NP-Hard Problems

Manufacturer: Course Technology
ProductGroup: Book
Binding: Hardcover

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ASIN: 0534949681

Book Description

This is the first book to fully address the study of approximation algorithms as a tool for coping with intractable problems. With chapters contributed by leading researchers in the field, this book introduces unifying techniques in the analysis of approximation algorithms.

Customer Reviews:

A good survey on approximation algorithms.......2000-05-09

Developing approximation algorithms for NP hard problems is now a very active field in Mathematical Programming and Theoretical Computer Science. This book is actually a collection of survey articles written by some of the foremost experts in this field.

Many of these developments are due to Mathemtical programming (primal dual, semidefinite programming et al). The most exciting of these has been the Goemans and Williamson algorithm for MAX CUT and MAX SAT. A good account of these techniques appears in Chapters 4 and 11.

On the other hand a sequence of unexpected results in complexity culminated in a proof that many of these problems cannot have polynomial approximation algorithms unless P=NP. A good survey of "Hardness of Approximations" appears in Chapter 10, written by Sanjeev Arora and Carsten Lund both of whom were responsible for some original developments in this field.

Book Description

Large-scale optimization is becoming increasingly important for students and professionals in electrical and industrial engineering, computer science, management science and operations research, and applied mathematics.

Linear Network Optimization presents a thorough treatment of classical approaches to network problems such as shortest path, max-flow, assignment, transportation, and minimum cost flow problems. It is the first text to clearly explain important recent algorithms such as auction and relaxation, proposed by the author and others for the solution of these problems. Its coverage of both theory and implementations make it particularly useful as a text for a graduate-level course on network optimization as well as a practical guide to state-of-the-art codes in the field.

Bertsekas focuses on the algorithms that have proved successful in practice and provides FORTRAN codes that implement them. The presentation is clear, mathematically rigorous, and economical. Many illustrations, examples, and exercises are included in the text.

Dimitri P. Bertsekas is Professor of Electrical Engineering and Computer Science at MIT.

Contents: Introduction. Simplex Methods. Dual Ascent Methods. Auction Algorithms. Performance and Comparisons. Appendixes.

Average customer rating:

not enough
Doubles as inexpensive textbook on operations research
Schaum's Outline of Operations Research
Solved problems book

Schaum's Outline of Operations Research
Richard Bronson , and Govindasami Naadimuthu
Manufacturer: McGraw-Hill
ProductGroup: Book
Binding: Paperback

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ASIN: 0070080208

Book Description

Tackling the broad range of allocation problems that actually confront engineers, programmers and analysts in today's business and industrial worlds, this book takes readers step-by-step through all the mathematical programming techniques--including the trailblazing Karmarkar algorithm--needed to excel in any operations research course. It's easy to see why the first edition of this invaluable study guide sole more than 35,000 copies! It cuts down study time while it builds essential skills.

Customer Reviews:

not enough.......2007-01-23

First of all, be careful, this is not a text book. It has a good presentation for problem solution. First, there are a some solved problems, then supplementary problems are coming. The answers of supplementary problems are at the end of the book.

This book might be useful for beginners. For every topic, there are easy problems, not specific problems similar to case studies. If you are over beginner degree, this book will not be useful for you. Especially, integer programming sections are not satisfactory. For instance, there isn't any facility location problem solution.

To sum-up this book may be useful for a beginner as a workbook.

Doubles as inexpensive textbook on operations research.......2006-04-15

Some of the primary tools used by operations researchers are statistics, optimization, stochastics, queueing theory, game theory, graph theory, and simulation. Because of the computational nature of these fields operations research also has ties to computer science, and thus this outline is useful to people from both fields. OR is concerned with optimization problems in which one seeks to maximize or minimize a specific quantity. The first part of this book is on optimization via linear, integer, and nonlinear programming. Next, network analysis is covered. Network analysis is the general name given to certain specific techniques which can be used for the planning, management and control of projects. Two different techniques for network analysis were developed independently in the late 1950's - PERT (Program Evaluation and Review Technique) and CPM (Critical Path Management). These techniques are also covered in the outline. The next subject tackled is that of inventory models - allowing shortages, allowing price discounts, risk conditions, etc., and their mathematical modeling. Game theory, decision theory, and dynamic programming are all explained in the context of inventory models and forecasting. Finally, there is coverage of Markov chains and queueing theory. Queuing Theory arises from the use of mathematical analysis to theoretically describe production processes along with statistical/probabilistic techniques to account for varying dynamic patterns within the stages of a productive process. The problem to be met is simply entitled "congestion", what happens when a system does not operate smoothly or efficiently.
I really liked this Schaum's outline, and I used it to teach myself most of the mathematical processes covered without the need for any additional resources. The theory is given in small doses along with very illustrative examples. The mathematics starts with simple algebra and works up to nothing more complex than probability and statistics. I highly recommend it for anybody enrolled in an operations research class as well as computer scientists and mathematics students that are studying any subset of the topics covered in this book.

Schaum's Outline of Operations Research.......2002-07-21

i found this book to be a very helpfull tool a long with my text book.it excels in its simplicity and a wide varity of examples and solved problems written in plain english.
hope you like it too.
thank you.
M. Madain.

Solved problems book.......2001-06-13

Originally the book of Richard Bronson(1982) was very useful for the solution of simple problems, then a difficult one, but it is always required a text book accompany this. The students of my classes need all the time solved problems to practice.

Schaum's Outline of Theory and Problems of Matrix Operations

Average customer rating:

if you need a review
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Excellent guide to matrix techniques
Delivers what is says on the box
Got matrix problems?

Schaum's Outline of Theory and Problems of Matrix Operations
Richard Bronson
Manufacturer: McGraw-Hill
ProductGroup: Book
Binding: Paperback

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ASIN: 0070079781

Book Description

If you want top grades and thorough understanding of matrix operations, this powerful study tool is the best tutor you can have! It takes you step-by-step through the subject and gives you 363 accompanying related problems with fully worked solutions. You also get plenty of practice problems to do on your own, working at your own speed. (Answers at the back show you how you're doing.) Famous for their clarity, wealth of illustrations and examples, and lack of dreary minutiae, Schaum’s Outlines have sold more than 30 million copies worldwide—and this guide will show you why!

Customer Reviews:

if you need a review.......2007-05-13

I got this book to try to make up for not haven taken linear algebra in school, because I am trying to learn to program in MatLab, whose name is derived from Matrix Labratory! So it works out, ie the book, to be a decent review for something I never actually studied!

Quant helper.......2007-02-13

Great book for review of linear algebra. I needed this book to check the results of code I had written for a quadratic beta routine.

Excellent guide to matrix techniques.......2005-12-03

Unlike the Schaum's outline of linear algebra, which is more about the physical interpretation of matrices as vectors, this Schaum's outline is good for learning techniques of solutions that were meant for large matrices. It is aimed at the applied mathematician, since there are not very many proofs as exercises. Instead, the user is taught the various algorithms used to solve matrix problems. The guide starts with very basic operations such as matrix addition, subtraction, and dot products. It then moves on to methods of solution for finding the determinant, eigenvalues and eigenvectors, and the functions of a matrix. What I particularly like about this guide is that in its more advanced section it shows in plain language how to implement singular value decomposition, the QR algorithm to compute eigenvalues, vector norms, LU decomposition, and other more advanced methods of solution that are not mentioned in basic linear algebra texts and are overloaded with theory in more advanced texts that lack practical examples. This book is an excellent companion to texts such as Trefethen and Bau's "Numerical Linear Algebra", since that book is short on worked examples and concentrates more on theory. The format of this guide is the same of most other Schaum's outlines- for each topic there are a few pages on motivation and the algorithms themselves, a section of worked problems, and a section of more problems with answers but not with complete solutions.

Delivers what is says on the box.......2005-08-29

Takes you right from the basics to complex stuff like QR decomposition and SVD. Very useful for programmers who want to gain knowledge on solving linear equations.

Got matrix problems?.......2002-08-27

If you do, this book is very helpful in that it gives a step-by-step approach to solving matrix operations problems. Although I wouldn't use this book by itself, I would recommend getting this to supplement the class. If you have already taken the class, then this is a good refresher or reference for you.

The topics covered are inversions, determinants, vectors, eigenvalues and eigenvectors, functions, square matrices, hermitian and positive definite matrices, canonical bases, unitary transformations, and nonnegative and patterned matrices, among other topics. As with other books in the Schaum's series, there are supplementary questions to test your knowledge and understanding. Most of the answers are in the back.

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