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 298
... estimates for c1 and c2 are correct but the estimates for both b1 and b2 are incorrect . Consider the fol- lowing four cases where the true values of b1 and b2 differ from their estimates by the same percentage : ( 1 ) both b1 and b2 ...
... estimates for c1 and c2 are correct but the estimates for both b1 and b2 are incorrect . Consider the fol- lowing four cases where the true values of b1 and b2 differ from their estimates by the same percentage : ( 1 ) both b1 and b2 ...
Page 487
... estimates for the respective activities ( where the most likely estimate is labeled as the ex- pected duration ) ... estimates . Using the " Cal- culate PERT " option on this toolbar recalculates " Duration " with the above formula ...
... estimates for the respective activities ( where the most likely estimate is labeled as the ex- pected duration ) ... estimates . Using the " Cal- culate PERT " option on this toolbar recalculates " Duration " with the above formula ...
Page 517
... estimated durations of the activities in this figure turn out to be the same as the mean durations given in Table 10.4 ( Sec . 10.4 ) when using the PERT three - estimate approach . Now suppose that the pessimistic estimates in Table ...
... estimated durations of the activities in this figure turn out to be the same as the mean durations given in Table 10.4 ( Sec . 10.4 ) when using the PERT three - estimate approach . Now suppose that the pessimistic estimates in Table ...
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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