## 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 177

(a) Demonstrate graphically that the

objective is to maximize Z = -jc, + x2. does the model have an optimal solution? If

so, find it. If not, explain why not. Ic) Repeat part {b) when the objective is to

maximize ...

(a) Demonstrate graphically that the

**feasible**region is unbounded. (b) If theobjective is to maximize Z = -jc, + x2. does the model have an optimal solution? If

so, find it. If not, explain why not. Ic) Repeat part {b) when the objective is to

maximize ...

Page 236

Weak duality property: If x is a

Glass Co. problem, one

...

Weak duality property: If x is a

**feasible**solution for the primal problem and y is a**feasible**solution for the dual problem, then ex ^ yb. For example, for the WyndorGlass Co. problem, one

**feasible**solution is x{ = 3, x2 = 3, which yields Z = ex = 24...

Page 246

TABLE 6.10 Classification of basic solutions Satisfies Condition for Optimality?

To review the reasoning behind this property, note that the dual solution (y*, z* - c

) must be

...

TABLE 6.10 Classification of basic solutions Satisfies Condition for Optimality?

To review the reasoning behind this property, note that the dual solution (y*, z* - c

) must be

**feasible**for the dual problem because the condition for optimality for 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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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