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 74
... plants produces the same 10 products and then sells them within its region . The de- mand ( sales potential ) for each of these products from each plant is known for each of the next 10 months . Although the amount of a product sold by a ...
... plants produces the same 10 products and then sells them within its region . The de- mand ( sales potential ) for each of these products from each plant is known for each of the next 10 months . Although the amount of a product sold by a ...
Page 103
... plant outside Detroit , MI , assembles two models from the family of midsized and luxury cars . The first model ... plant , is currently deciding the production schedule for the next month . Specifically , she must decide how many Fam ...
... plant outside Detroit , MI , assembles two models from the family of midsized and luxury cars . The first model ... plant , is currently deciding the production schedule for the next month . Specifically , she must decide how many Fam ...
Page 388
... ( Plant ) 3 37 30 27 21 0 45 Demand 20 30 30 40 75 Management has specified that every plant should be assigned at least one of the prod- ucts . There are more products ( four ) than plants ( three ) , so one of the plants will need to be ...
... ( Plant ) 3 37 30 27 21 0 45 Demand 20 30 30 40 75 Management has specified that every plant should be assigned at least one of the prod- ucts . There are more products ( four ) than plants ( three ) , so one of the plants will need to be ...
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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 described dual problem dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau flow following problem formulation functional constraints Gaussian elimination given 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 simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero