## Introduction to Operations Research, Volume 1CD-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 81

A3.1

A3.1

**shows**how this problem would be formulated with LINGO . The first line of this formulation is just a comment describing the model . Note that the comment is preceded by an exclamation point and ended by a semicolon .Page 183

the lists of materials requirements for each pattern , and the lists of demand forecasts for each pattern determined by customer surveys at fashion

the lists of materials requirements for each pattern , and the lists of demand forecasts for each pattern determined by customer surveys at fashion

**shows**. She remembers the hectic and sometimes nightmarish days of designing the fall ...Page 997

How- ever , since there commonly are a few no -

How- ever , since there commonly are a few no -

**shows**, the airline should accept a few more than 125 reservations . On those occasions when more than 125 people arrive to take the flight , the airline will find volunteers who are ...### 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 algebraic algorithm allocation allowable range artificial variables assignment problem augmenting path basic solution Big M method changes coefficients column Consider the following constraint boundary corresponding CPLEX decision variables dual problem dynamic programming entering basic variable example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal goal programming graphically identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LP relaxation lution Maximize Maximize Z maximum flow problem Minimize needed node nonbasic variables objective function obtained optimal solution optimality test path Plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices slack variables solve this model Solver spreadsheet step subproblem surplus variables tion transportation problem transportation simplex method weeks Wyndor Glass x₁ zero