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 115
Frederick S. Hillier, Gerald J. Lieberman. variables . To illustrate , consider the first functional constraint in the Wyndor Glass Co. example of Sec . 3.1 X1 ≤ 4 . The slack variable for this constraint is defined to be X3 = 4 - X1 ...
Frederick S. Hillier, Gerald J. Lieberman. variables . To illustrate , consider the first functional constraint in the Wyndor Glass Co. example of Sec . 3.1 X1 ≤ 4 . The slack variable for this constraint is defined to be X3 = 4 - X1 ...
Page 116
... slack variables are x3 = 1 , X4 = 8 , and = X5 5 . A basic solution is an augmented corner - point solution . To illustrate , consider the corner - point infeasible solution ( 4 , 6 ) in Fig . 4.1 . Augmenting it with the resulting ...
... slack variables are x3 = 1 , X4 = 8 , and = X5 5 . A basic solution is an augmented corner - point solution . To illustrate , consider the corner - point infeasible solution ( 4 , 6 ) in Fig . 4.1 . Augmenting it with the resulting ...
Page 212
... slack variables and the information they give . It is a direct result of the initialization , where the ith slack variable x , + ; is given a coefficient of +1 in Eq . ( i ) and a coefficient of 0 in every other equation [ including Eq ...
... slack variables and the information they give . It is a direct result of the initialization , where the ith slack variable x , + ; is given a coefficient of +1 in Eq . ( i ) and a coefficient of 0 in every other equation [ including Eq ...
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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 corresponding cost Courseware CPF solution CPLEX decision variables 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 interior-point iteration leaving basic variable linear programming model linear programming problem LINGO LP relaxation lution Maximize subject 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 simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ zero