## 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 166

The two basic factors that determine the performance of an algorithm on a real prob- lem are the average computer time per

The two basic factors that determine the performance of an algorithm on a real prob- lem are the average computer time per

**iteration**and the number of**iterations**. Our next comparisons concern these factors .Page 330

7.7 the reconfigured feasible re- gion after rescaling based on the trial solution just obtained for

7.7 the reconfigured feasible re- gion after rescaling based on the trial solution just obtained for

**iteration**3. ... 7.5 , 7.6 , and 7.7 how the se- quence of**iterations**and rescaling have the effect of " sliding " the optimal solution ...Page 371

At each

At each

**iteration**, after the difference for every row and column remaining un- der consideration is calculated and displayed , the largest difference is circled and the small- est unit cost in its row or column is enclosed in a box .### 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