Introduction to Mathematical Programming Applications and Algorithms, Volume 1 (with CD-ROM and InfoTrac),9780534359645

Introduction to Mathematical Programming Applications and Algorithms, Volume 1 (with CD-ROM and InfoTrac)

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Edition: 4th
ISBN13: 9780534359645
ISBN10: 0534359647
Format: Hardcover
Pub. Date: 2002-10-28
Publisher(s): INGRAM
List Price: $355.86

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Summary

Authors Wayne Winston and Munirpallam Venkataramanan emphasize model-formulation and model-building skills as well as interpretation of computer software output. Focusing on deterministic models, this book is designed for the first half of an operations research sequence. A subset of Winston's best-selling OPERATIONS RESEARCH, INTRODUCTION TO MATHEMATICAL PROGRAMMING offers self-contained chapters that make it flexible enough for one- or two-semester courses ranging from advanced beginning to intermediate in level. The book has a strong computer orientation and emphasizes model-formulation and model-building skills. Every topic includes a corresponding computer-based modeling and solution method and every chapter presents the software tools needed to solve realistic problems. LINDO, LINGO, and Premium Solver for Education software packages are available with the book.

Table of Contents

Preface ix
An Introduction to Model-Building
1(10)
An Introduction to Modeling
1(4)
The Seven-Step Model-Building Process
5(1)
CITGO Petroleum
6(1)
San Francisco Police Department Scheduling
7(2)
GE Capital
9(2)
Basic Linear Algebra
11(38)
Matrices and Vectors
11(9)
Matrices and Systems of Linear Equations
20(2)
The Gauss-Jordan Method for Solving Systems of Linear Equations
22(10)
Linear Independence and Linear Dependence
32(4)
The Inverse of a Matrix
36(6)
Determinants
42(7)
Introduction to Linear Programming
49(78)
What Is a Linear Programming Problem?
49(7)
The Graphical Solution of Two-Variable Linear Programming Problems
56(7)
Special Cases
63(5)
A Diet Problem
68(4)
A Work-Scheduling Problem
72(4)
A Capital Budgeting Problem
76(6)
Short-Term Financial Planning
82(3)
Blending Problems
85(10)
Production Process Models
95(5)
Using Linear Programming to Solve Multiperiod Decision Problems: An Inventory Model
100(5)
Multiperiod Financial Models
105(4)
Multiperiod Work Scheduling
109(18)
The Simplex Algorithm and Goal Programming
127(100)
How to Convert an LP to Standard Form
127(3)
Preview of the Simplex Algorithm
130(4)
Direction of Unboundedness
134(2)
Why Does an LP Have an Optimal bfs
136(4)
The Simplex Algorithm
140(9)
Using the Simplex Algorithm to Solve Minimization Problems
149(3)
Alternative Optimal Solutions
152(2)
Unbounded LPs
154(4)
The LINDO Computer Package
158(5)
Matrix Generators, LINGO, and Scaling of LPs
163(5)
Degeneracy and the Convergence of the Simplex Algorithm
168(4)
The Big M Method
172(6)
The Two-Phase Simplex Method
178(6)
Unrestricted-in-Sign Variables
184(6)
Karmarkar's Method for Solving LPs
190(1)
Multiattribute Decision Making in the Absence of Uncertainty: Goal Programming
191(11)
Using the Excel Solver to Solve LPs
202(25)
Sensitivity Analysis: An Applied Approach
227(35)
A Graphical Introduction to Sensitivity Analysis
227(5)
The Computer and Sensitivity Analysis
232(14)
Managerial Use of Shadow Prices
246(2)
What Happens to the Optimalz-Value If the Current Basis Is No Longer Optimal?
248(14)
Sensitivity Analysis and Duality
262(98)
A Graphical Introduction to Sensitivity Analysis
262(5)
Some Important Formulas
267(8)
Sensitivity Analysis
275(14)
Sensitivity Analysis When More Than One Parameter Is Changed: The 100% Rule
289(6)
Finding the Dual of an LP
295(7)
Economic Interpretation of the Dual Problem
302(2)
The Dual Theorem and Its Consequences
304(9)
Shadow Prices
313(10)
Duality and Sensitivity Analysis
323(2)
Complementary Slackness
325(4)
The Dual Simplex Method
329(6)
Data Envelopment Analysis
335(25)
Transportation, Assignment, and Transshipment Problems
360(53)
Formulating Transportation Problems
360(13)
Finding Basic Feasible Solutions for Transportation Problems
373(9)
The Transportation Simplex Method
382(8)
Sensitivity Analysis for Transportation Problems
390(3)
Assignment Problems
393(7)
Transshipment Problems
400(13)
Network Models
413(62)
Basic Definitions
413(1)
Shortest Path Problems
414(5)
Maximum Flow Problems
419(12)
CPM and PERT
431(19)
Minimum Cost Network Flow Problems
450(6)
Minimum Spanning Tree Problems
456(3)
The Network Simplex Method
459(16)
Integer Programming
475(87)
Introduction to Integer Programming
475(2)
Formulating Integer Programming Problems
477(35)
The Branch-and-Bound Method for Solving Pure Integer Programming Problems
512(11)
The Branch-and-Bound Method for Solving Mixed Integer Programming Problems
523(1)
Solving Knapsack Problems by the Branch-and-Bound Method
524(3)
Solving Combinatorial Optimization Problems by the Branch-and-Bound Method
527(13)
Implicit Enumeration
540(5)
The Cutting Plane Algorithm
545(17)
Advanced Topics in Linear Programming
562(48)
The Revised Simplex Algorithm
562(5)
The Product Form of the Inverse
567(3)
Using Column Generation to Solve Large-Scale LPs
570(6)
The Dantzig-Wolfe Decomposition Algorithm
576(17)
The Simplex Method for Upper-Bounded Variables
593(4)
Karmarkar's Method for Solving LPs
597(13)
Game Theory
610(43)
Two-Person Zero-Sum and Constant-Sum Games: Saddle Points
610(4)
Two-Person Zero-Sum Games: Randomized Strategies, Domination, and Graphical Solution
614(9)
Linear Programming and Zero-Sum Games
623(11)
Two-Person Nonconstant-Sum Games
634(5)
Introduction to n-Person Game Theory
639(2)
The Core of an-Person Game
641(3)
The Shapley Value
644(9)
Nonlinear Programming
653(97)
Review of Differential Calculus
653(6)
Introductory Concepts
659(14)
Convex and Concave Functions
673(7)
Solving NLPs with One Variable
680(12)
Golden Section Search
692(6)
Unconstrained Maximization and Minimization with Several Variables
698(5)
The Method of Steepest Ascent
703(3)
Lagrange Multipliers
706(7)
The Kuhn-Tucker Conditions
713(10)
Quadratic Programming
723(8)
Separable Programming
731(5)
The Method of Feasible Directions
736(2)
Pareto Optimality and Tradeoff Curves
738(12)
Deterministic Dynamic Programming
750(50)
Two Puzzles
750(1)
A Network Problem
751(7)
An Inventory Problem
758(5)
Resource Allocation Problems
763(11)
Equipment Replacement Problems
774(4)
Formulating Dynamic Programming Recursions
778(12)
Using EXCEL to Solve Dynamic Programming Problems
790(10)
Heuristic Techniques
800(23)
Complexity Theory
800(4)
Introduction to Heuristic Procedures
804(1)
Simulated Annealing
805(3)
Genetic Search
808(7)
Tabu Search
815(6)
Comparison of Heuristics
821(2)
Solving Optimization Problems with the Evolutionary Solver
823(43)
Price Bundling, Index Function, Match Function, and Evolutionary Solver
823(7)
More Nonlinear Pricing Models
830(6)
Locating Warehouses
836(3)
Solving Other Combinatorial Problems
839(2)
Production Scheduling at John Deere
841(5)
Assigning Workers to Jobs with the Evolutionary Solver
846(5)
Cluster Analysis
851(6)
Fitting Curves
857(3)
Discriminant Analysis
860(6)
Neural Networks
866(25)
Introduction to Neural Networks
866(4)
Examples of the Use of Neural Networks
870(1)
Why Neural Nets Can Beat Regression: The XOR Example
871(3)
Estimating Neural Nets with PREDICT
874(8)
Using Genetic Algorithms to Optimize a Neural Network
882(2)
Using Genetic Algorithms to Determine Weights for a Back Propagation Network
884(7)
Appendix: Cases 891(22)
Case 1 Help, I'm Not Getting Any Younger
892(1)
Case 2 Solar Energy for Your Home
892(1)
Case 3 Golf-Sport: Managing Operations
893(3)
Case 4 Vision Corporation: Production Planning and Shipping
896(1)
Case 5 Material Handling in a General Mail-Handling Facility
897(3)
Case 6 Selecting Corporate Training Programs
900(3)
Case 7 Best Chip: Expansion Strategy
903(2)
Case 8 Emergency Vehicle Location in Springfield
905(1)
Case 9 System Design: Project Management
906(1)
Case 10 Modular Design for the Help-You Company
907(2)
Case 11 Brite Power: Capacity Expansion
909(4)
Index 913

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