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 537
... calculations for the three alternatives are summarized below . x2 = E : = F : x2 = G : X2 f2 ( C , E ) = CCE + f ( E ) = 3 + 4 = 7 . f2 ( C , F ) CCF + f ( F ) = 2 + 7 = 9 . f2 ( C , G ) = cc.o + f ( G ) = 4 + 6 = 10 . The minimum of ...
... calculations for the three alternatives are summarized below . x2 = E : = F : x2 = G : X2 f2 ( C , E ) = CCE + f ( E ) = 3 + 4 = 7 . f2 ( C , F ) CCF + f ( F ) = 2 + 7 = 9 . f2 ( C , G ) = cc.o + f ( G ) = 4 + 6 = 10 . The minimum of ...
Page 917
... calculations yourself for other cases , as il- lustrated by the following example . = Example 1 - How Many Repairers ... Calculation of E ( TC ) in dollars 18.4 DECISION MODELS 917.
... calculations yourself for other cases , as il- lustrated by the following example . = Example 1 - How Many Repairers ... Calculation of E ( TC ) in dollars 18.4 DECISION MODELS 917.
Page 1041
... calculations to obtain these forecasts when the smoothing constant is a 0.25 and the trend smoothing constant is ẞ = 0.25 . ( Use hand calculations rather than an Excel template . ) 20.6-2 . * Exponential smoothing with trend , with a ...
... calculations to obtain these forecasts when the smoothing constant is a 0.25 and the trend smoothing constant is ẞ = 0.25 . ( Use hand calculations rather than an Excel template . ) 20.6-2 . * Exponential smoothing with trend , with a ...
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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 dual problem dual simplex method dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal programming 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 slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero