Title:
Operations research : applications and algorithms
Personal Author:
Edition:
3rd ed
Publication Information:
Belmont, CA : Duxbury Press, 1994
Physical Description:
1v + 1 computer disk (DSK 887)
ISBN:
9780534209711
9789814040259
General Note:
Paperback edition is not accompanied by diskette
Subject Term:
Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
---|---|---|---|---|---|
Searching... | 30000000090641 | T57.6 W56 1994 | Open Access Book | Book | Searching... |
Searching... | 30000010196253 | T57.6 W56 1994 | Open Access Book | Book | Searching... |
Searching... | 30000005022912 | T57.6 W56 1994 | Open Access Book | Book | Searching... |
On Order
Table of Contents
1 Introduction to model building |
An Introduction to Modeling |
The Seven-Step Model-Building Process |
Examples |
2 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 |
3 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 |
4 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 |
5 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? |
6 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 |
7 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 |
8 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 |
9 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 |
10 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 |
11 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 |
12 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 |
13 Decision making under uncertainty |
Decision Criteria |
Utility Theory |
Flaws in Expe |