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
Note that it is possible to produce a silk camisole without producing a silk blouse and a cot- ton miniskirt without producing a cotton sweater . The demand forecasts indicate that some items have limited demand .
Note that it is possible to produce a silk camisole without producing a silk blouse and a cot- ton miniskirt without producing a cotton sweater . The demand forecasts indicate that some items have limited demand .
Page 364
The imaginary supply quantity for this dummy source would be the amount by which the sum of the demands exceeds the ... Similarly , the for- mulation for Hollyglass does not require any adjustments because its demand ( 60 ) ex- ceeds ...
The imaginary supply quantity for this dummy source would be the amount by which the sum of the demands exceeds the ... Similarly , the for- mulation for Hollyglass does not require any adjustments because its demand ( 60 ) ex- ceeds ...
Page 933
The forecasting job you did for us two months ago really allowed us to understand the weekly demand for the center , but we still have not been able to get a grasp on the staffing problem . We used both historical data and your ...
The forecasting job you did for us two months ago really allowed us to understand the weekly demand for the center , but we still have not been able to get a grasp on the staffing problem . We used both historical data and your ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity additional algorithm allowable amount apply assigned basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider Construct corresponding cost CPF solution decision variables described determine developed dual problem entering equations estimates example feasible feasible region feasible solutions FIGURE final flow formulation functional constraints given gives goal identify illustrate increase indicates initial iteration linear programming linear programming model Maximize million Minimize month needed node objective function obtained operations optimal optimal solution original parameters path perform plant possible presented primal problem Prob procedure profit programming problem provides range resource respective resulting revised sensitivity analysis shown shows side simplex method simplex tableau slack solve step Table tableau tion unit values weeks Wyndor Glass x₁ zero