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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Results 1-3 of 83
Page 494
... weeks , cost = $ 430,000 . Crash point : time = 6 weeks , cost = $ 490,000 . Maximum reduction in time = Crash cost per week saved = = 8-6 = 2 weeks . - $ 490,000 $ 430,000 = $ 30,000 . 2 Table 10.7 gives the corresponding data obtained ...
... weeks , cost = $ 430,000 . Crash point : time = 6 weeks , cost = $ 490,000 . Maximum reduction in time = Crash cost per week saved = = 8-6 = 2 weeks . - $ 490,000 $ 430,000 = $ 30,000 . 2 Table 10.7 gives the corresponding data obtained ...
Page 519
... weeks , with penalties imposed for late delivery . The project involves 10 activities ( labeled A , B , . . . , J ) ... weeks 32 weeks В 22 weeks 28 weeks 26 weeks 36 weeks 14 weeks 16 weeks 32 weeks 32 weeks 40 weeks 52 weeks 12 weeks 16 ...
... weeks , with penalties imposed for late delivery . The project involves 10 activities ( labeled A , B , . . . , J ) ... weeks 32 weeks В 22 weeks 28 weeks 26 weeks 36 weeks 14 weeks 16 weeks 32 weeks 32 weeks 40 weeks 52 weeks 12 weeks 16 ...
Page 522
... weeks hence . Using the CPM method of time - cost trade - offs , he has obtained the following data . $ 30 million $ 20 million $ 24 million $ 43 million $ 30 million Activity Normal Time Crash Time Normal Cost Crash Cost A 5 weeks 3 weeks ...
... weeks hence . Using the CPM method of time - cost trade - offs , he has obtained the following data . $ 30 million $ 20 million $ 24 million $ 43 million $ 30 million Activity Normal Time Crash Time Normal Cost Crash Cost A 5 weeks 3 weeks ...
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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