## 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 119

Choose x , and x2 to be the

Choose x , and x2 to be the

**nonbasic variables**( = 0 ) for the initial BF solution : ( 0 , 0 , 4 , 12 , 18 ) . Not optimal , because increasing either**nonbasic variable**( x , or x2 ) increases Z. Not optimal , because moving along ...Page 199

Each constraint has an indicating variable that completely indicates ( by whether its value is zero ) whether that ... Each basic solution has m basic variables , and the rest of the variables are

Each constraint has an indicating variable that completely indicates ( by whether its value is zero ) whether that ... Each basic solution has m basic variables , and the rest of the variables are

**nonbasic variables**set equal to zero .Page 200

Thus , it is possible for a variable to be zero and still not be a

Thus , it is possible for a variable to be zero and still not be a

**nonbasic variable**for the current BF solution . ( This case corresponds to a CPF solution that satisfies another constraint boundary equation in addition to its n ...### What people are saying - Write a review

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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