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 179
... Minimize Z = 5,000x1 + 7,000x2 , subject to and -2x1 + x2 = 1 x1 = 2x2 ≥ 1 X2 ≥ 0 . I ( a ) Using the two - phase method , work through phase 1 step by step . c ( b ) Use a software package based on the simplex method to for- mulate ...
... Minimize Z = 5,000x1 + 7,000x2 , subject to and -2x1 + x2 = 1 x1 = 2x2 ≥ 1 X2 ≥ 0 . I ( a ) Using the two - phase method , work through phase 1 step by step . c ( b ) Use a software package based on the simplex method to for- mulate ...
Page 415
... Minimize the total distance traveled , as in the Seervada Park example . 2. Minimize the total cost of a sequence of activities . ( Problem 9.3-2 is of this type . ) 3. Minimize the total time of a sequence of activities . ( Problems ...
... Minimize the total distance traveled , as in the Seervada Park example . 2. Minimize the total cost of a sequence of activities . ( Problem 9.3-2 is of this type . ) 3. Minimize the total time of a sequence of activities . ( Problems ...
Page 713
... Minimize subject to and x1 + x2 = 10 z = 2x2 + x2 , and X2 ≥ 0 . ( a ) Obtain the KKT conditions for this problem . ( b ) Use the KKT conditions to check whether ( x1 , x2 ) = ( } , } ) is an optimal solution . ( c ) Use the KKT ...
... Minimize subject to and x1 + x2 = 10 z = 2x2 + x2 , and X2 ≥ 0 . ( a ) Obtain the KKT conditions for this problem . ( b ) Use the KKT conditions to check whether ( x1 , x2 ) = ( } , } ) is an optimal solution . ( c ) Use the KKT ...
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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