## 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

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Page 195

Consider any linear programming problem with n decision variables and a bounded

Consider any linear programming problem with n decision variables and a bounded

**feasible region**. A CPF solution lies at the intersection of n constraint boundaries ( and satisfies the other constraints as well ) .Page 198

largement of the

largement of the

**feasible region**to the right of ( , 5 ) . Consequently , the adjacent CPF solutions for ( 2 , 6 ) now are ( 0 , 6 ) and ( š , 5 ) , and again neither is better than ( 2 , 6 ) . However , another CPF solution ( 4 ...Page 1200

... 1155 Blending program , 56 – 57 Bolzano search plan , 671 Bottom - up approach forecasting , 1014 Boundary of the

... 1155 Blending program , 56 – 57 Bolzano search plan , 671 Bottom - up approach forecasting , 1014 Boundary of the

**feasible region**, 190 – 191 , 193 – 194 , 704 Boundary repulsion term , 703 Bounded**feasible region**, 593 Bounding ...### What people are saying - Write a review

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### Contents

SUPPLEMENT TO APPENDIX 3 | 3 |

Problems | 6 |

SUPPLEMENT TO CHAPTER | 18 |

Copyright | |

52 other sections not shown

### Other editions - View all

Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |

### 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 constraint Construct corresponding cost CPF solution decision variables demand described determine distribution dual problem entering equal equations estimates example feasible feasible region 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 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 unit values weeks Wyndor Glass zero