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 184
... demand because once the pants and shirts go out of style , the company cannot sell them . TrendLines can produce less than the forecasted demand , however , since the company is not required to meet the demand . The cashmere sweater ...
... demand because once the pants and shirts go out of style , the company cannot sell them . TrendLines can produce less than the forecasted demand , however , since the company is not required to meet the demand . The cashmere sweater ...
Page 933
... demand into average hourly demand by dividing the weekly demand by the number of hours in the workweek . We then staffed the center to meet this average hourly demand by taking into account the average number of calls a representative ...
... demand into average hourly demand by dividing the weekly demand by the number of hours in the workweek . We then staffed the center to meet this average hourly demand by taking into account the average number of calls a representative ...
Page 949
... demand rate is planned ( as with the production line in the TV speakers example in Sec . 19.1 ) , in- terruptions and variations in the demand rate still are likely to occur . It also is very dif- ficult to satisfy the assumption that ...
... demand rate is planned ( as with the production line in the TV speakers example in Sec . 19.1 ) , in- terruptions and variations in the demand rate still are likely to occur . It also is very dif- ficult to satisfy the assumption that ...
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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