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 267
Analyzing Simultaneous Changes in Right - Hand Sides . When multiple b ; values are changed simultaneously , the formula b * = S * b can again be used to see how the righthand sides change in the final tableau .
Analyzing Simultaneous Changes in Right - Hand Sides . When multiple b ; values are changed simultaneously , the formula b * = S * b can again be used to see how the righthand sides change in the final tableau .
Page 273
Analyzing Simultaneous Changes in Objective Function Coefficients . Regardless of whether x ; is a basic or nonbasic variable , the allowable range to stay optimal for c ; is valid only if this objective function coefficient is the only ...
Analyzing Simultaneous Changes in Objective Function Coefficients . Regardless of whether x ; is a basic or nonbasic variable , the allowable range to stay optimal for c ; is valid only if this objective function coefficient is the only ...
Page 316
The set of basic variables in the optimal solution still changes ( as increases ) only where the slope of Z * ( 0 ) changes . However , in contrast to the preceding case , the values of these variables now change as a ( linear ) ...
The set of basic variables in the optimal solution still changes ( as increases ) only where the slope of Z * ( 0 ) changes . However , in contrast to the preceding case , the values of these variables now change as a ( linear ) ...
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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 allocation allowable range artificial variables assignment problem augmenting path basic solution Big M method changes coefficients column Consider the following constraint boundary corresponding CPLEX decision variables 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 graphically identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LP relaxation lution Maximize Maximize Z maximum flow problem Minimize needed node nonbasic variables objective function obtained optimal solution optimality test path Plant presented in Sec primal problem Prob procedure range to stay resource right-hand sides sensitivity analysis shadow prices slack variables solve this model Solver spreadsheet step subproblem surplus variables tion transportation problem transportation simplex method weeks Wyndor Glass x₁ zero