## Introduction to Operations ResearchCD-ROM contains: Student version of MPL Modeling System and its solver CPLEX -- MPL tutorial -- Examples from the text modeled in MPL -- Examples from the text modeled in LINGO/LINDO -- Tutorial software -- Excel add-ins: TreePlan, SensIt, RiskSim, and Premium Solver -- Excel spreadsheet formulations and templates. |

### From inside the book

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Page 214

Ignoring row 0 for the moment , we see that these algebraic operations amount to pre- multiplying rows 1 to 3 of the initial

Ignoring row 0 for the moment , we see that these algebraic operations amount to pre- multiplying rows 1 to 3 of the initial

**tableau**by the matrix 1 0 0 0 12 0 2 0 1 1 Rows 1 to 3 of the initial**tableau**are 1 0 1 0 0 4 Old rows 1-3 ...Page 216

Even when the simplex method has gone through hundreds or thousands of iterations , the coefficients of the slack vari- ables in the final

Even when the simplex method has gone through hundreds or thousands of iterations , the coefficients of the slack vari- ables in the final

**tableau**will reveal how this**tableau**has been obtained from the initial**tableau**.Page 259

These coefficients of the slack variables necessarily are unchanged with the same alge- braic operations originally performed by the simplex method because the coefficients of these same variables in the initial

These coefficients of the slack variables necessarily are unchanged with the same alge- braic operations originally performed by the simplex method because the coefficients of these same variables in the initial

**tableau**are unchanged .### What people are saying - Write a review

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### Other editions - View all

Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |

### Common terms and phrases

activity additional algorithm allowable amount apply assigned basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider Construct corresponding cost CPF solution decision variables described determine developed dual problem entering equations estimates example feasible feasible region feasible solutions FIGURE final flow formulation functional constraints given gives goal identify illustrate increase indicates initial iteration linear programming linear programming model Maximize million Minimize month needed node objective function obtained operations optimal optimal solution original parameters path perform plant possible presented primal problem Prob procedure profit programming problem provides range resource respective resulting revised sensitivity analysis shown shows side simplex method simplex tableau slack solve step Table tableau tion unit values weeks Wyndor Glass x₁ zero