## 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 369

1. From the rows and columns still under consideration , select the next basic variable ( allocation ) according to some criterion . 2. Make that allocation large enough to exactly use up the

1. From the rows and columns still under consideration , select the next basic variable ( allocation ) according to some criterion . 2. Make that allocation large enough to exactly use up the

**remaining**supply ...Page 370

This first iteration leaves a supply of 20

This first iteration leaves a supply of 20

**remaining**in row 1 , so next select X1,1 + 1 = X12 to be a basic variable . Because this supply is no larger than the demand of 20 in column 2 , all of it is allocated , X12 20 , and this row ...Page 371

At each iteration , after the difference for every row and column

At each iteration , after the difference for every row and column

**remaining**under consideration is calculated and displayed , the largest difference is circled and the smallest unit cost in its row or column is enclosed in a box .### 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