{
"item_title" : "Introduction to Linear Optimization and Extensions with Matlab(r)",
"item_author" : [" Roy H. Kwon "],
"item_description" : "This book fills the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty. It includes two major ways of including parameter uncertainty: stochastic linear programming and robust linear optimization. Presenting basics before theory, the author offers a rigorous development of linear programming theory and methods. The text contains financial optimization case studies, an extensive bibliography, and MATLAB(R) exercises, with the code available on the book's CRC Press web page. ",
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"price_data" : {
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Overview
This book fills the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty. It includes two major ways of including parameter uncertainty: stochastic linear programming and robust linear optimization. Presenting basics before theory, the author offers a rigorous development of linear programming theory and methods. The text contains financial optimization case studies, an extensive bibliography, and MATLAB(R) exercises, with the code available on the book's CRC Press web page.
This item is Non-Returnable
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Details
- ISBN-13: 9781439862636
- ISBN-10: 143986263X
- Publisher: CRC Press
- Publish Date: September 2013
- Dimensions: 9.3 x 6.3 x 0.9 inches
- Shipping Weight: 1.4 pounds
- Page Count: 362
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