## 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 298

Consider the following four cases where the true values of b , and be differ from

their

their

Consider the following four cases where the true values of b , and be differ from

their

**estimates**by the same percentage : ( 1 ) both b , and b2 are smaller thantheir

**estimates**, ( 2 ) both b , and b2 are larger than their**estimates**, ( 3 ) b , is ...Page 487

Similarly , an approximate formula for u is M 0 + 4m + p 6 Intuitively , this formula

is placing most of the weight on the most likely

weights on the other two

u ...

Similarly , an approximate formula for u is M 0 + 4m + p 6 Intuitively , this formula

is placing most of the weight on the most likely

**estimate**and then small equalweights on the other two

**estimates**. MS Project provides the option of calculatingu ...

Page 517

Using the PERT three -

activities are as follows : optimistic

days , pessimistic

and ...

Using the PERT three -

**estimate**approach , the three**estimates**for one of theactivities are as follows : optimistic

**estimate**30 days , most likely**estimate**36days , pessimistic

**estimate**48 days . What are the resulting**estimates**of the meanand ...

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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 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