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 154
... shadow price by y * coefficient of the ith slack variable in row 0 of the final simplex tableau . = To illustrate , for the Wyndor Glass Co. problem , = Resource i = production capacity of Plant i ( i 1 , 2 , 3 ) being made available to ...
... shadow price by y * coefficient of the ith slack variable in row 0 of the final simplex tableau . = To illustrate , for the Wyndor Glass Co. problem , = Resource i = production capacity of Plant i ( i 1 , 2 , 3 ) being made available to ...
Page 155
... shadow prices , including y = 0. ) Now note in Fig . 4.8 why y = 0. Because the constraint on resource 1 , x1 ≤ 4 , is not binding on the optimal solution ( 2 , 6 ) , there is a surplus of this resource . Therefore , increasing b1 ...
... shadow prices , including y = 0. ) Now note in Fig . 4.8 why y = 0. Because the constraint on resource 1 , x1 ≤ 4 , is not binding on the optimal solution ( 2 , 6 ) , there is a surplus of this resource . Therefore , increasing b1 ...
Page 267
... Shadow prices are in- valuable for this kind of exploration . However , shadow prices remain valid for evaluating the effect of such changes on Z only within certain ranges of changes . For each b1 , the allowable range to stay feasible ...
... Shadow prices are in- valuable for this kind of exploration . However , shadow prices remain valid for evaluating the effect of such changes on Z only within certain ranges of changes . For each b1 , the allowable range to stay feasible ...
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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 described 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 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 simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero