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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Page 15
... optimal solution ) to find a good suboptimal solution . This is most often the case when the time or cost required to find an optimal solution for an adequate model of the problem would be very large . In recent years , great progress ...
... optimal solution ) to find a good suboptimal solution . This is most often the case when the time or cost required to find an optimal solution for an adequate model of the problem would be very large . In recent years , great progress ...
Page 35
... optimal solutions if the objective function were changed to Z = 3x1 + 2x2 . Z = 18 = 3x + 2x2 X2 Maximize Z = 3x1 + ... solution that plays the key role when the simplex method searches for an optimal solution . A corner - point ...
... optimal solutions if the objective function were changed to Z = 3x1 + 2x2 . Z = 18 = 3x + 2x2 X2 Maximize Z = 3x1 + ... solution that plays the key role when the simplex method searches for an optimal solution . A corner - point ...
Page 223
... feasible solution is optimal , it must be a CPF solution . ( b ) The number of CPF solutions is at least ( m + n ) ! m ! n ! ( c ) If a CPF solution has adjacent CPF solutions that are better ( as measured by Z ) , then one of these ...
... feasible solution is optimal , it must be a CPF solution . ( b ) The number of CPF solutions is at least ( m + n ) ! m ! n ! ( c ) If a CPF solution has adjacent CPF solutions that are better ( as measured by Z ) , then one of these ...
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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 corresponding cost Courseware CPF solution CPLEX decision variables dual problem dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau flow following problem formulation functional constraints Gaussian elimination given graphical identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LINGO LP relaxation lution Maximize subject 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 right-hand sides sensitivity analysis shadow prices simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ zero