## 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 |

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Page 294

( as in Table 6.23 ) for sensitivity analysis of the

analysis to verify the allowable ranges ... of the 16 combinations of unit profits

considered in assembly

from ...

( as in Table 6.23 ) for sensitivity analysis of the

**supplies**be( f ) Use graphicalanalysis to verify the allowable ranges ... of the 16 combinations of unit profits

considered in assembly

**supply**. parts ( c ) and ( d ) where both unit profits differfrom ...

Page 364

s production scheduling problem , where there was excess

there is excess demand capacity . Consequently , rather than introducing a

dummy destination to " receive " the unused

needed ...

s production scheduling problem , where there was excess

**supply**capacity . Nowthere is excess demand capacity . Consequently , rather than introducing a

dummy destination to " receive " the unused

**supply**capacity , the adjustmentneeded ...

Page 985

economy is that of

management of a multiechelon inventory system one step further by also

considering ...

**Supply**Chain Management Another key concept that has emerged in this globaleconomy is that of

**supply**chain management . This concept pushes themanagement of a multiechelon inventory system one step further by also

considering ...

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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