## 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

Results 1-3 of 80

Page 159

The "Final Value" column

the optimal solution. The next two columns

value of the right-hand side (&,-) for each constraint. When just one bt value is ...

The "Final Value" column

**gives**the value of each constraint's left-hand side forthe optimal solution. The next two columns

**give**the shadow price and the currentvalue of the right-hand side (&,-) for each constraint. When just one bt value is ...

Page 170

The column to the right of these values

discussed reduced costs in this chapter because the information they provide can

also be gleaned from the allowable range to slay optimal for the coefficients in

the ...

The column to the right of these values

**gives**the reduced costs. We have notdiscussed reduced costs in this chapter because the information they provide can

also be gleaned from the allowable range to slay optimal for the coefficients in

the ...

Page 231

For the primal problem, each column (except the Right Side column)

coefficients of a single variable in the respective constraints and then in the

objective function, whereas each row (except the bottom one)

parameters for a ...

For the primal problem, each column (except the Right Side column)

**gives**thecoefficients of a single variable in the respective constraints and then in the

objective function, whereas each row (except the bottom one)

**gives**theparameters for a ...

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### Contents

SUPPLEMENT TO APPENDIX 3 | 3 |

Problems | 6 |

An Algorithm for the Assignment Problem | 18 |

Copyright | |

44 other sections not shown

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### Common terms and phrases

activity additional algorithm alternative amount analysis apply assigned assumed basic variable begin BF solution bound calculate called changes coefficients column complete Consider constraints Construct corresponding cost CPF solution customers decision demand described determine developed distribution entering equations estimated example expected feasible FIGURE final flow formulation given gives hour identify illustrate increase indicates initial inventory iteration linear programming machine Maximize maximum mean million Minimize month needed node objective function obtained operations optimal optimal solution original parameter path payoff perform plant player possible presented Prob probability problem procedure profit programming problem queueing respectively resulting shown shows side simplex method solution solve step strategy Table tableau tion transportation unit weeks