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 108
... begin work at the beginning of the 7 A.M. to 9 A.M. shift , 9 A.M. to 11 A.M. shift , 11 A.M. to 1 P.M. shift , or 1 P.M. to 3 P.M. shift . The part - time employees work for 4 hours , only answer calls , and only speak English . They ...
... begin work at the beginning of the 7 A.M. to 9 A.M. shift , 9 A.M. to 11 A.M. shift , 11 A.M. to 1 P.M. shift , or 1 P.M. to 3 P.M. shift . The part - time employees work for 4 hours , only answer calls , and only speak English . They ...
Page 511
... begin until the exterior siding is there on which to paint . How- ever , it certainly is possible to begin painting on one wall while the exterior siding still is being put up to form the other walls . Thus , activity H actually can begin ...
... begin until the exterior siding is there on which to paint . How- ever , it certainly is possible to begin painting on one wall while the exterior siding still is being put up to form the other walls . Thus , activity H actually can begin ...
Page 583
... begin production for various new or- ders ? When should we begin marketing various new products ? When should we make various capital investments to expand our production capacity ? For any such activity , the decision about when to ...
... begin production for various new or- ders ? When should we begin marketing various new products ? When should we make various capital investments to expand our production capacity ? For any such activity , the decision about when to ...
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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