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 256
just how any changes in the original model would change the numbers in the final sim- plex tableau ( assuming that the same sequence of algebraic operations originally per- formed by the simplex method were to be duplicated ) .
just how any changes in the original model would change the numbers in the final sim- plex tableau ( assuming that the same sequence of algebraic operations originally per- formed by the simplex method were to be duplicated ) .
Page 264
When the fundamental insight ( Table 6.17 ) is applied , the effect of this change in b2 on the original final simplex tableau ( middle of Table 6.19 ) is that the entries in the right - side column change to the following values : 4 Z ...
When the fundamental insight ( Table 6.17 ) is applied , the effect of this change in b2 on the original final simplex tableau ( middle of Table 6.19 ) is that the entries in the right - side column change to the following values : 4 Z ...
Page 290
( d ) Suppose that the original problem is changed to D.I 6.6-3 . Consider the following problem . Minimize subject to W = 5y1 + 4y2 , Maximize Z = 3x1 + 3x2 + 4x3 , subject to and 6x1 + 2x2 + 5x3 ≤ 25 3x1 + 3x2 + 5x3≤ 20 X2 ≥ 0 ...
( d ) Suppose that the original problem is changed to D.I 6.6-3 . Consider the following problem . Minimize subject to W = 5y1 + 4y2 , Maximize Z = 3x1 + 3x2 + 4x3 , subject to and 6x1 + 2x2 + 5x3 ≤ 25 3x1 + 3x2 + 5x3≤ 20 X2 ≥ 0 ...
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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 assigned basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider Construct corresponding cost CPF solution decision variables described determine developed dual problem entering 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 linear programming model Maximize million Minimize month needed node objective function obtained operations optimal optimal solution original parameters path perform plant possible presented primal problem Prob procedure profit programming problem provides range resource respective resulting revised sensitivity analysis shown shows side simplex method simplex tableau slack solve step Table tableau tion unit values weeks Wyndor Glass x₁ zero