## 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 215

Note how this matrix is reproduced exactly in the box below it as the coefficients

of the slack variables in rows 1 to 3 of the new (

line. What this portion of the tableau reveals is how the entire

except ...

Note how this matrix is reproduced exactly in the box below it as the coefficients

of the slack variables in rows 1 to 3 of the new (

**final**) tableau shown on the thirdline. What this portion of the tableau reveals is how the entire

**final**tableau (except ...

Page 216

Even when the simplex method has gone through hundreds or thousands of

iterations, the coefficients of the slack variables in the

how this tableau has been obtained from the initial tableau. Furthermore, the

same ...

Even when the simplex method has gone through hundreds or thousands of

iterations, the coefficients of the slack variables in the

**final**tableau will revealhow this tableau has been obtained from the initial tableau. Furthermore, the

same ...

Page 259

However, because other portions of the initial tableau have changed, there will

be changes in the rest of the

6.17, we calculate the revised numbers in the rest of the

1 0 ...

However, because other portions of the initial tableau have changed, there will

be changes in the rest of the

**final**tableau as well. Using the formulas in Table6.17, we calculate the revised numbers in the rest of the

**final**tableau as follows:1 0 ...

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activity additional algorithm alternative amount analysis apply assignment assumed basic variable begin BF solution calculate called changes coefficients column complete Consider constraints Construct corresponding cost CPF solution customers decision demand described determine developed distribution entering equations estimated example expected feasible FIGURE final flow formulation given gives hour identify illustrate increase indicates initial inventory iteration linear programming machine Maximize mean million Minimize month needed node objective function obtained operations optimal optimal solution original parameter path payoff perform plant player possible presented Prob probability problem procedure profit programming problem queueing respectively resulting shown shows side simplex method solution solve step strategy Table tableau tion transportation unit waiting weeks