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 98
... hour week . In addition , by union contract , the number of full - time employees can never drop below 20. Nonunion ... hour , while each part- time employee earns $ 10 per hour . Management wishes to know what mix of each of the three ...
... hour week . In addition , by union contract , the number of full - time employees can never drop below 20. Nonunion ... hour , while each part- time employee earns $ 10 per hour . Management wishes to know what mix of each of the three ...
Page 107
... hour of the day . Since all appointment and registration - related calls would be received by the call center , the ... hour of a weekday . The following table provides the forecasts . Work Shift Average Number of Calls 7 A.M. - 9 A.M. ...
... hour of the day . Since all appointment and registration - related calls would be received by the call center , the ... hour of a weekday . The following table provides the forecasts . Work Shift Average Number of Calls 7 A.M. - 9 A.M. ...
Page 884
... hour 0.00037 hour 0.238 hour 0.029 hour 1 0.154 hour 0.00793 hour 0.325 hour 0.033 hour 1 W3 1.033 hours 0.06542 hour 0.889 hour 0.048 hour μ fore , W1 must equal W for the corresponding one - class model ( the M / M / s model in Sec ...
... hour 0.00037 hour 0.238 hour 0.029 hour 1 0.154 hour 0.00793 hour 0.325 hour 0.033 hour 1 W3 1.033 hours 0.06542 hour 0.889 hour 0.048 hour μ fore , W1 must equal W for the corresponding one - class model ( the M / M / s model in Sec ...
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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