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 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 ...
Page 523
... estimated durations and costs of these activities are shown below in the left column . START A E B F FINISH Activity Estimated Duration Estimated Cost Activity Estimated Duration Estimated Cost ABCDE 6 weeks $ 420,000 A 6 weeks 2 weeks ...
... estimated durations and costs of these activities are shown below in the left column . START A E B F FINISH Activity Estimated Duration Estimated Cost Activity Estimated Duration Estimated Cost ABCDE 6 weeks $ 420,000 A 6 weeks 2 weeks ...
Page 1138
... estimated by redefining Y = Σ ( n − 1 ) 2 TM „ . n = 2 This point estimate , along with the point estimate of La ( the first moment of N1 ) just de- scribed , can then be used to estimate the variance of Nq . Specifically , because of ...
... estimated by redefining Y = Σ ( n − 1 ) 2 TM „ . n = 2 This point estimate , along with the point estimate of La ( the first moment of N1 ) just de- scribed , can then be used to estimate the variance of Nq . Specifically , because of ...
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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 CPF solution CPLEX decision variables described dual problem dynamic programming entering basic variable example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal goal programming graphical identify increase initial BF solution integer interior-point 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 right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ zero