Introduction to Operations Research, Volume 1CD-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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TABLE 4.6 First two simplex tableaux for the Wyndor Glass Co. problem Coefficient of : Basic Variable Iteration Eq . 2 Right Side X1 X2 X3 X4 X5 Z 1 0 1 Х3 X4 Xg 0 ( 0 ) ( 1 ) ( 2 ) ( 3 ) O O -3 1 0 3 -5 0 2 2 0 0 1 0 0 0 1 0 4 12 18 0 ...
TABLE 4.6 First two simplex tableaux for the Wyndor Glass Co. problem Coefficient of : Basic Variable Iteration Eq . 2 Right Side X1 X2 X3 X4 X5 Z 1 0 1 Х3 X4 Xg 0 ( 0 ) ( 1 ) ( 2 ) ( 3 ) O O -3 1 0 3 -5 0 2 2 0 0 1 0 0 0 1 0 4 12 18 0 ...
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X2 10 = 8 Z = 45 = 7.5x1 + 5x2 ( or Z = 18 = 3x1 + 2x2 ) Z = 36 = 3x1 + 5x2 = ( 2,6 ) optimal Z = 30 = 0xı + 5x2 = 4 FIGURE 4.9 This graph demonstrates the sensitivity analysis of C and C2 for the Wyndor Glass Co. problem .
X2 10 = 8 Z = 45 = 7.5x1 + 5x2 ( or Z = 18 = 3x1 + 2x2 ) Z = 36 = 3x1 + 5x2 = ( 2,6 ) optimal Z = 30 = 0xı + 5x2 = 4 FIGURE 4.9 This graph demonstrates the sensitivity analysis of C and C2 for the Wyndor Glass Co. problem .
Page 197
5.1 for the Wyndor Glass Co. example . For the CPF solution ( 2 , 6 ) , its adjacent CPF solutions are ( 0 , 6 ) and ( 4 , 3 ) , and neither has a better value of Z than ( 2 , 6 ) does . This outcome implies that none of the other CPF ...
5.1 for the Wyndor Glass Co. example . For the CPF solution ( 2 , 6 ) , its adjacent CPF solutions are ( 0 , 6 ) and ( 4 , 3 ) , and neither has a better value of Z than ( 2 , 6 ) does . This outcome implies that none of the other CPF ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
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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 direction 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