Introduction to Operations Research, Volume 1CD-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 388
... 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 assigned two products . Plant 3 has only enough excess capacity to produce one prod ...
... 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 assigned two products . Plant 3 has only enough excess capacity to produce one prod ...
Page 389
... 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 assigned two products . Plant 3 has only enough excess capacity to produce one prod ...
... 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 assigned two products . Plant 3 has only enough excess capacity to produce one prod ...
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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 CPF solution CPLEX decision variables described dual problem dynamic programming entering basic variable example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal goal programming graphical identify increase initial BF solution integer interior-point 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 right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ zero