## 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 89

Page 267

Analyzing Simultaneous

are changed simultaneously, the formula b* = S*b can again be used to see how

the right- hand sides

Analyzing Simultaneous

**Changes**in Right-Hand Sides. When multiple bf valuesare changed simultaneously, the formula b* = S*b can again be used to see how

the right- hand sides

**change**in the final tableau. If all these right-hand sides still ...Page 273

Analyzing Simultaneous

of whether xj is a basic or nonbasic variable, the allowable range to stay optimal

for Cj is valid only if this objective function coefficient is the only one being ...

Analyzing Simultaneous

**Changes**in Objective Function Coefficients. Regardlessof whether xj is a basic or nonbasic variable, the allowable range to stay optimal

for Cj is valid only if this objective function coefficient is the only one being ...

Page 316

The set of basic variables in the optimal solution still

only where the slope of Z*(0)

case, the values of these variables now

between the ...

The set of basic variables in the optimal solution still

**changes**(as 0 increases)only where the slope of Z*(0)

**changes**. However, in contrast to the precedingcase, the values of these variables now

**change**as a (linear) function of 0between the ...

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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