## Introduction to Operations Research, Volume 1-- This classic, field-defining text is the market leader in Operations Research -- and it's now updated and expanded to keep professionals a step ahead -- Features 25 new detailed, hands-on case studies added to the end of problem sections -- plus an expanded look at project planning and control with PERT/CPM -- A new, software-packed CD-ROM contains Excel files for examples in related chapters, numerous Excel templates, plus LINDO and LINGO files, along with MPL/CPLEX Software and MPL/CPLEX files, each showing worked-out examples |

### From inside the book

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Page 757

15.5 where the two lines intersect is the crossover point where the decision shifts

from one

probability increases . To find this point , we set E [ Payoff ( drill ) ] = E [ Payoff (

sell ) ...

15.5 where the two lines intersect is the crossover point where the decision shifts

from one

**alternative**( sell the land ) to the other ( drill for oil ) as the priorprobability increases . To find this point , we set E [ Payoff ( drill ) ] = E [ Payoff (

sell ) ...

Page 900

Consider the finite queue variation of the MIM / s model . a mean of 15 minutes (

for

this model . vided by the number of operators in the crew ( for

Consider the finite queue variation of the MIM / s model . a mean of 15 minutes (

for

**Alternatives**1 and 2 ) or 15 minutes diDerive the expression for Lq ... 17.6 forthis model . vided by the number of operators in the crew ( for

**Alternative**3 ) .Page 928

For both

slow but inexpensive ) . ... Restaurant revenue per month is given by $ 6,000 / W ,

( b ) Find these same measures of performance for

...

For both

**alternatives**, the cars arrive acment are X ( fast but expensive ) and Y (slow but inexpensive ) . ... Restaurant revenue per month is given by $ 6,000 / W ,

( b ) Find these same measures of performance for

**Alternative**2 . where W is the...

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### Common terms and phrases

activity additional algorithm 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 region 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 shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit weeks Wyndor Glass zero