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 94
... maximize Z = = −x1 + x2 , does the model have an optimal solution ? If so , find it . If not , explain why not . ( c ) Repeat part ( b ) when the objective is to maximize Z = x1 = x2 . ( d ) For objective functions where this model has ...
... maximize Z = = −x1 + x2 , does the model have an optimal solution ? If so , find it . If not , explain why not . ( c ) Repeat part ( b ) when the objective is to maximize Z = x1 = x2 . ( d ) For objective functions where this model has ...
Page 176
... Z = 2x1 + 3x2 , X2 ≥ 0 . 4.4-6 . Consider the following problem . Maximize Z = 2x1 + 4x2 + 3x3 , subject to 3x1 + 4x2 + 2x3 ≤ 60 2x1 + x2 + 2x3 ≤40 x1 + 3x2 + 2x3 ≤ 80 and X2 ≥ 0 , D. ( a ) Work through the simplex method step ...
... Z = 2x1 + 3x2 , X2 ≥ 0 . 4.4-6 . Consider the following problem . Maximize Z = 2x1 + 4x2 + 3x3 , subject to 3x1 + 4x2 + 2x3 ≤ 60 2x1 + x2 + 2x3 ≤40 x1 + 3x2 + 2x3 ≤ 80 and X2 ≥ 0 , D. ( a ) Work through the simplex method step ...
Page 177
... maximize Z -x1 + x2 , does the model have an optimal solution ? If so , find it . If not , explain why not . ( c ) Repeat part ( b ) when the objective is to maximize Z = X ] X2 . ( d ) For objective functions where this model has no ...
... maximize Z -x1 + x2 , does the model have an optimal solution ? If so , find it . If not , explain why not . ( c ) Repeat part ( b ) when the objective is to maximize Z = X ] X2 . ( d ) For objective functions where this model has no ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity algebraic algorithm allowable range artificial variables b₂ basic solution c₁ c₂ changes coefficients column Consider the following cost Courseware CPLEX decision variables dual problem dual simplex method dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal programming graphical identify increase initial BF solution integer iteration leaving basic variable linear programming model linear programming problem LINGO LP relaxation lution Maximize Z maximum flow problem Minimize needed node nonbasic variables nonnegativity constraints objective function obtained optimal solution optimality test parameters path plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices shown slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero