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 134
... Wyndor Glass Co. problem in Sec . 3.1 ) . We show below the resulting artificial problem ( before augmenting ) next to the real problem . The Real Problem Maximize Z = 3x1 + 5x2 , The Artificial Problem 183x12x2 . 3x15x2Mx5 , Define is ...
... Wyndor Glass Co. problem in Sec . 3.1 ) . We show below the resulting artificial problem ( before augmenting ) next to the real problem . The Real Problem Maximize Z = 3x1 + 5x2 , The Artificial Problem 183x12x2 . 3x15x2Mx5 , Define is ...
Page 260
... Wyndor Glass Co. model Coefficient of : Right Basic Variable Eq . Z X1 X2 X3 X4 X5 Side 3 Z ( 0 ) 1 -2 0 0 1 54 2 1 1 1 X3 ( 1 ) 0 0 1 6 3 3 3 Revised final tableau 1 X2 ( 2 ) 0 0 1 0 0 12 2 X1 ( 3 ) 0 2/3 1 0 0 3 13 -2 Z ( 0 ) 1 0 0 ...
... Wyndor Glass Co. model Coefficient of : Right Basic Variable Eq . Z X1 X2 X3 X4 X5 Side 3 Z ( 0 ) 1 -2 0 0 1 54 2 1 1 1 X3 ( 1 ) 0 0 1 6 3 3 3 Revised final tableau 1 X2 ( 2 ) 0 0 1 0 0 12 2 X1 ( 3 ) 0 2/3 1 0 0 3 13 -2 Z ( 0 ) 1 0 0 ...
Page 561
... Wyndor Glass Co. linear programming problem . ( 3 ) f * ( 4 , 12 , 18 ) = max_ { 3x1 + ƒ * ( 4 − x1 , 12 , 18 – 3x1 ) } . x1≤4 3x , ≤18 Equation ( 1 ) will be used to solve the stage 2 problem . Equation ( 2 ) shows the basic dynamic ...
... Wyndor Glass Co. linear programming problem . ( 3 ) f * ( 4 , 12 , 18 ) = max_ { 3x1 + ƒ * ( 4 − x1 , 12 , 18 – 3x1 ) } . x1≤4 3x , ≤18 Equation ( 1 ) will be used to solve the stage 2 problem . Equation ( 2 ) shows the basic dynamic ...
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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