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Operations Research Applications and Algorithms

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ISBN-10: 0534423558

ISBN-13: 9780534423551

Edition: 4th 2004

Authors: Wayne L. Winston, Jeffrey B. Goldberg

List price: $4.99
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This textbook owes much of its success to its practical orientation and consistent emphasis on model formulation and model building. It moves beyond a mere study of algorithms without sacrificing the rigour that lecturers desire.
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Book details

List price: $4.99
Edition: 4th
Copyright year: 2004
Publisher: Brooks/Cole
Binding: Digital, Other 
Pages: 1418

Wayne L. Winston is a professor of Decision Sciences at Indiana University's Kelley School of Business and the recipient of more than 30 teaching awards. For the past 20 years, Wayne has also taught Fortune 500 companies how to use Excel to make smarter business decisions. He has written 15 books on Excel, management science, and mathematics in sports.

Introduction to model building
An Introduction to Modeling
The Seven-Step Model-Building Process
Examples
Basic linear algebra
Matrices and Vectors
Matrices and Systems of Linear Equations
The Gauss-Jordan Method for Solving Systems of Linear Equations
Linear Independence and Linear Dependence
The Inverse of a Matrix
Determinants
Introduction to linear programming
What is a Linear Programming Problem? The Graphical Solution of Two-Variable Linear Programming Problems
Special Cases
A Diet Problem
A Work-Scheduling Problem
A Capital Budgeting Problem
Short-term Financial Planning
Blending Problems
Production Process Models
Using Linear Programming to Solve Multiperiod Decision Problems: An Inventory Model
Multiperiod Financial Models
Multiperiod Work Scheduling
The simplex algorithm and goal programming
How to Convert an LP to Standard Form
Preview of the Simplex Algorithm
The Simplex Algorithm
Using the Simplex Algorithm to Solve Minimization Problems
Alternative Optimal Solutions
Unbounded LPs
The LINDO Computer Package
Matrix Generators, LINGO, and Scaling of LPs
Degeneracy and the Convergence of the Simplex Algorithm
The Big M Method
The Two-Phase Simplex Method
Unrestricted-in-Sign Variables
Karmarkar''s Method for Solving LPs
Multiattribute Decision-Making in the Absence of Uncertainty: Goal Programming
Solving LPs with Spreadsheets
Sensitivity analysis: an applied approach
A Graphical Introduction to Sensitivity Analysis
The Computer and Sensitivity Analysis
Managerial Use of Shadow Prices
What Happens to the Optimal z-value if the Current Basis is No Longer Optimal?
Sensitivity analysis and duality
A Graphical Introduction to Sensitivity Analysis
Some Important Formulas
Sensitivity Analysis
Sensitivity Analysis When More Than One Parameter is Changed: The 100% Rule
Finding the Dual of an LP
Economic Interpretation of the Dual Problem
The Dual Theorem and Its Consequences
Shadow Prices
Duality and Sensitivity Analysis
Transportation, assignment, and transshipment problems
Formulating Transportation Problems
Finding Basic Feasible Solutions for Transportation Problems
The Transportation Simplex Method
Sensitivity Analysis for Transportation Problems
Assignment Problems
Transshipment Problems
Network models
Basic Definitions
Shortest Path Problems
Maximum Flow Problems
CPM and PERT
Minimum Cost Network Flow Problems
Minimum Spanning Tree Problems
The Network Simplex Method
Integer programming
Introduction to Integer Programming
Formulation Integer Programming Problems
The Branch-and-Bound Method for Solving Pure Integer Programming Problems
The Branch-and-Bound Method for Solving Mixed Integer Programming Problems
Solving Knapsack Problems by the Branch-and-Bound Method
Solving Combinatorial Optimization Problems by the Branch-and-Bound Method
Implicit Enumeration
The Cutting Plane Algorithm
Advanced topics in linear programming
The Revised Simplex Algorithm
The Product Form of the Inverse
Using Column Generation to Solve Large-Scale LPs
The Dantzig-Wolfe Decomposition Algorithm
The Simplex Methods for Upper-Bounded Variables
Karmarkar''s Method for Solving LPs
Nonlinear programming
Review of Differential Calculus
Introductory Concepts
Convex and Concave Functions
Solving NLPs with One Variable
Golden Section Search
Unconstrained Maximization and Minimization with Several Variables
The Method of Steepest Ascent
Lagrange Multiples
The Kuhn-Tucker Conditions
Quadratic Programming
Separable Programming
The Method of Feasible Directions
Pareto Optimality and Tradeoff Curves
Review of calculus and probability
Review of Integral Calculus
Differentiation of Integrals
Basic Rules of Probability
Bayes'' Rule
Random Variables
Mean Variance and Covariance
The Normal Distribution
Z-Transforms
Review Problems
Decision making under uncertainty
Decision Criteria
Utility Theory
Flaws in Expe