Introduction to linear optimization and extensions with MATLAB
 Responsibility
 Roy H. Kwon.
 Language
 English.
 Publication
 Boca Raton, FL : CRC Press, c2014.
 Physical description
 xviii, 343 p. : ill. ; 25 cm.
 Series
 Operations research series.
Access
Creators/Contributors
 Author/Creator
 Kwon, Roy H., author.
Contents/Summary
 Bibliography
 Includes bibliographical references (p. 329335) and index.
 Contents

 Linear Programming Introduction General Linear Programming Problems More Linear Programming Examples Exercises Computational Project Geometry of Linear Programming Introduction Geometry of the Feasible Set Extreme Points and Basic Feasible Solutions Resolution (Representation) Theorem Exercises The Simplex Method Introduction Simplex Method Development Generating an Initial Basic Feasible Solution (TwoPhase and Big M Methods) Degeneracy and Cycling Revised Simplex Method Complexity of the Simplex Method Simplex Method MATLAB Code Exercises Duality Theory Introduction Motivation for Duality Forming the Dual Problem for General Linear Programs Weak and Strong Duality Theory Complementary Slackness Duality and the Simplex Method Economic Interpretation of the Dual Sensitivity Analysis Exercises DantzigWolfe Decomposition Introduction Decomposition for Block Angular Linear Programs Master Problem Reformulation Restricted Master Problem and the Revised Simplex Method DantzigWolfe Decomposition DantzigWolfe MATLAB Code Exercises Interior Point Methods Introduction Linear Programming Optimality Conditions PrimalDual Interior Point Strategy The PredictorCorrector Variant of the PrimalDual Interior Point Method PrimalDual Interior Point Method in MATLAB Exercises Quadratic Programming Introduction QP Model Structure QP Application: Financial Optimization Solving Quadratic Programs Using MATLAB Optimality Conditions for Quadratic Programming Exercises Linear Optimization under Uncertainty Introduction Stochastic Programming More Stochastic Programming Examples Robust Optimization Exercises A Linear Algebra Review Bibliography.
 (source: Nielsen Book Data)
 Publisher's Summary
 Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with MATLAB(R) provides a concrete and intuitive yet rigorous introduction to modern linear optimization. In addition to fundamental topics, the book discusses current linear optimization technologies such as predictorpath following interior point methods for both linear and quadratic optimization as well as the inclusion of linear optimization of uncertainty i.e. stochastic programming with recourse and robust optimization. The author introduces both stochastic programming and robust optimization as frameworks to deal with parameter uncertainty. The author's unusual approachdeveloping these topics in an introductory bookhighlights their importance. Since most applications require decisions to be made in the face of uncertainty, the early introduction of these topics facilitates decision making in real world environments. The author also includes applications and case studies from finance and supply chain management that involve the use of MATLAB. Even though there are several LP texts in the marketplace, most do not cover data uncertainty using stochastic programming and robust optimization techniques. Most emphasize the use of MS Excel, while this book uses MATLAB which is the primary tool of many engineers, including financial engineers. The book focuses on stateoftheart methods for dealing with parameter uncertainty in linear programming, rigorously developing theory and methods. But more importantly, the author's meticulous attention to developing intuition before presenting theory makes the material come alive.
(source: Nielsen Book Data)
Subjects
Bibliographic information
 Publication date
 2014
 Title Variation
 Linear optimization and extensions with MATLAB
 Series
 The operations research series
 ISBN
 9781439862636 (hbk.)
 143986263X (hbk.)
 1439862648 (ebook)
 9781439862643 (ebook)