PDF Download Model Building in Mathematical Programming
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Model Building in Mathematical Programming
PDF Download Model Building in Mathematical Programming
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From the Back Cover
Model Building in Mathematical Programming covers a wide range of applications in many diverse areas, such as operational research, systems engineering, agriculture, energy planning, mining, logistics and distribution, computer science, management science, statistics, applied mathematics and mathematical biology. Model Building in Mathematical Programming aims to provide students with a solid foundation in the principles of model building as well as the more mathematical, algorithmic side of the subject which is conventionally taught. It is also intended to provide managers with a fairly non-technical appreciation of the scope and limitations of mathematical programming. Praise for the 4th Edition: 'Such a text, and this is the only one of this type I know of, should be the basis of all instruction in Mathematical Programming.' Journal of the Royal Statistical Society 'An excellent introduction ... for students of business administration and people who want to see the utility of operations research.' European Journal of Operational Research This new edition includes: New sections on stochastic programming, column generation and constraint logic programming as well as many enhancements of former sections. 29 detailed practical problems, including 5 new problems, to enable the reader to build mathematical programming models using the numerical data.
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About the Author
H. Paul Williams, London School of Economics, UK
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Product details
Paperback: 432 pages
Publisher: Wiley; 5 edition (March 4, 2013)
Language: English
ISBN-10: 1118443330
ISBN-13: 978-1118443330
Product Dimensions:
6 x 0.8 x 9.1 inches
Shipping Weight: 1.2 pounds (View shipping rates and policies)
Average Customer Review:
5.0 out of 5 stars
8 customer reviews
Amazon Best Sellers Rank:
#318,742 in Books (See Top 100 in Books)
The fifth edition came out in 2013 and it's exactly what I was looking for. It's current and it feels current. It's well-written and organized, with many worked examples, including 29 problems in chapters 12-14.These 29 examples are pretty clever, and make up all of Section II (chapters 12-14). For example, 12.1 describes a food manufacturing (blending) problem in sufficient detail for you to create a model. 13.1 describes the model, broken down into a one-month solution (13.1.1) and the more-complex ongoing production problem (31.1.2). Last, 14.1 describes the answer you get from the model in 13.1.I'm not trained in OR, but have a bit of practical experience in creating a model in GMPL, and the book's exactly what I needed. It talks about mathematical modeling in general and touches on things like constraint programming, then covers designing a linear model, structured linear models (i.e. linear models with sub models), and various linear model applications. Then it covers the interpretation of linear models, and looks at non-linear models before falling into the longest part (two chapters) on integer programming. That's Section I, which is followed by Section II and its 29 examples.If you're new to linear programming or have some self-taught experience, this is a perfect book. It has a lot of insights, well-organized, and the examples are very valuable. I'm totally satisfied!
This book has no code. It isn't written for any particular solver. It simply (and critically importantly) helps you think about a very broad range of problems and then do the math formulation for them. With that you can implement the result in whatever API for whatever solver you want. A really great book that has and will stand the test of time (with a few small exceptions given some new modeling techniques).
Very useful book for modeling, especially the chapters with 30 examples
It is a perfect book for who want to learn Mathematical Modeling and Mathematical Programming for linear and non linear optimization and multigoal programming
The first edition was excellent and Paul Williams has added scope and more examples to each new edition. An essential companion for all Operations Research students and for experienced professionals.
Great book!!
Nice book for beginners not much complicated math. I would have loved to have it in hard cover though. Have to see how long the paperback is gonna last with my intense use.
Great examples, concise and well structured reference
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