## 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. |

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Page 156

A main purpose of sensitivity analysis is to identify the sensitive

. , those that cannot be changed without changing the optimal solution ) . The

sensitive

A main purpose of sensitivity analysis is to identify the sensitive

**parameters**( i . e. , those that cannot be changed without changing the optimal solution ) . The

sensitive

**parameters**are the**parameters**that need to be estimated with special ...Page 255

existent , so that the

more than quick rules of thumb provided by harassed line personnel . The data

may even represent deliberate overestimates or underestimates to protect the ...

existent , so that the

**parameters**in the original formulation may represent littlemore than quick rules of thumb provided by harassed line personnel . The data

may even represent deliberate overestimates or underestimates to protect the ...

Page 284

Because 0 = 1 is the maximum realistic value of 0 , this indicates that c , and ca

together are insensitive

6 . 21 . There is no need to try to estimate these

Because 0 = 1 is the maximum realistic value of 0 , this indicates that c , and ca

together are insensitive

**parameters**with respect to the Variation 2 model in Table6 . 21 . There is no need to try to estimate these

**parameters**more closely unless ...### What people are saying - Write a review

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### Contents

SUPPLEMENT TO APPENDIX 3 | 3 |

Problems | 6 |

An Algorithm for the Assignment Problem | 18 |

Copyright | |

59 other sections not shown

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### Common terms and phrases

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