## 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 158

Adjustable Cells Final Reduced Cell Name Value Cost $ C $ 9 Solution Doors 2 0 $ D $ 9 Solution Windows 6 0 Objective

Adjustable Cells Final Reduced Cell Name Value Cost $ C $ 9 Solution Doors 2 0 $ D $ 9 Solution Windows 6 0 Objective

**Allowable Allowable**Coefficient increase Decrease 3 4.5 3 5 1E + 30 3 Constraints FIGURE 4.10 The sensitivity report ...Page 266

4.7 , this range of values for b2 is referred to as its

4.7 , this range of values for b2 is referred to as its

**allowable**range to stay feasible . For any bi , recall from Sec . 4.7 that its**allowable**range to stay feasible is the range of values over which the current optimal BF solution ...Page 272

Since zi = y * A1 , this immediately yields the same

Since zi = y * A1 , this immediately yields the same

**allowable**range . Figure 6.3 provides graphical insight into why Ci s 7 is the**allowable**range . At ( 1 = 7 , the objective function becomes 2 = 7.5x , + 5x2 = 2.5 ( 3x + 2x2 ) ...### 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