Roy H. Kwon

Introduction to Linear Optimization and Extensions with MATLAB (eBook, PDF)

• Format: PDF

Produktbeschreibung

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 exercises, with the code available on the book's CRC Press web page.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 362
• Erscheinungstermin: 5. September 2013
• Englisch
• ISBN-13: 9781482204346
• Artikelnr.: 57100666

Autorenporträt

Roy H Kwon is a professor at University of Toronto - St. George Campus, Canada.

Inhaltsangabe

FUNDAMENTALS: Geometry of Linear Optimization. Simplex Method. Duality and
Sensitivity Analysis. EXTENSIONS: Decomposition in Linear Optimization.
Quadratic Optimization. Interior Point Methods. ROBUST STRATEGIES FOR
LINEAR OPTIMIZATION: Stochastic Programming. Robust Linear Optimization.