Introduction to Operations ResearchCD-ROM contains: Student version of MPL Modeling System and its solver CPLEX -- MPL tutorial -- Examples from the text modeled in MPL -- Examples from the text modeled in LINGO/LINDO -- Tutorial software -- Excel add-ins: TreePlan, SensIt, RiskSim, and Premium Solver -- Excel spreadsheet formulations and templates. |
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Page 158
Adjustable Cells Final Reduced Objective Allowable Allowable Cell Name Value
Cost Coefficient Increase Decrease $ C $ 9 Solution Doors 2 0 3 4.5 3 $ D $ 9
Solution Windows 6 0 5 1E + 30 3 Constraints FIGURE 4.10 The sensitivity report
...
Adjustable Cells Final Reduced Objective Allowable Allowable Cell Name Value
Cost Coefficient Increase Decrease $ C $ 9 Solution Doors 2 0 3 4.5 3 $ D $ 9
Solution Windows 6 0 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 allowable range to stay
feasible . For any bị , recall from Sec . 4.7 that its allowable range to stay feasible
is the range of values over which the current optimal BF solution ' ( with adjusted
...
4.7 , this range of values for b2 is referred to as its allowable range to stay
feasible . For any bị , recall from Sec . 4.7 that its allowable range to stay feasible
is the range of values over which the current optimal BF solution ' ( with adjusted
...
Page 272
Since zit = y * Aį , this immediately yields the same allowable range . Figure 6.3
provides graphical insight into why ci s 7 is the allowable range . At cı = 72 , the
objective function becomes Z = 7.5x2 + 5x2 = 2.5 ( 3x1 + 2x2 ) , so the optimal ...
Since zit = y * Aį , this immediately yields the same allowable range . Figure 6.3
provides graphical insight into why ci s 7 is the allowable range . At cı = 72 , the
objective function becomes Z = 7.5x2 + 5x2 = 2.5 ( 3x1 + 2x2 ) , so the optimal ...
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activity additional algorithm allocation allowable amount apply assignment basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider constraint Construct corresponding cost CPF solution decision variables demand described determine distribution dual problem entering equal equations estimates example feasible feasible region feasible solutions 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 revised shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit values weeks Wyndor Glass zero