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 111
Frederick S. Hillier, Gerald J. Lieberman. TABLE 4.1 Adjacent CPF solutions for each CPF solution of the Wyndor Glass Co. problem CPF Solution Its Adjacent CPF Solutions ( 0 , 6 ) and ( 4 , 0 ) ( 0 , 0 ) ( 0 , 6 ) ( 2,6 ) ( 4,3 ) ( 4 , 0 ) ...
Frederick S. Hillier, Gerald J. Lieberman. TABLE 4.1 Adjacent CPF solutions for each CPF solution of the Wyndor Glass Co. problem CPF Solution Its Adjacent CPF Solutions ( 0 , 6 ) and ( 4 , 0 ) ( 0 , 0 ) ( 0 , 6 ) ( 2,6 ) ( 4,3 ) ( 4 , 0 ) ...
Page 113
... of the feasible region . ' The only restriction is that the problem must possess CPF solutions . This is ensured if the feasible region is bounded . The next focus is on which adjacent CPF solution to 4.1 THE ESSENCE OF THE SIMPLEX METHOD ...
... of the feasible region . ' The only restriction is that the problem must possess CPF solutions . This is ensured if the feasible region is bounded . The next focus is on which adjacent CPF solution to 4.1 THE ESSENCE OF THE SIMPLEX METHOD ...
Page 174
... CPF so- lution to move to from the current CPF solution , it only con- siders adjacent CPF solutions because one of them is likely to be an optimal solution . ( e ) To choose the new CPF solution to move to from the current CPF solution ...
... CPF so- lution to move to from the current CPF solution , it only con- siders adjacent CPF solutions because one of them is likely to be an optimal solution . ( e ) To choose the new CPF solution to move to from the current CPF solution ...
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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