Introduction to Operations ResearchCD-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. |
From inside the book
Results 1-3 of 97
Page 216
... coefficients of the slack vari- ables in the final tableau will reveal how this tableau has been obtained from the initial tableau . Furthermore , the same algebraic operations would give these same coefficients even if the values of ...
... coefficients of the slack vari- ables in the final tableau will reveal how this tableau has been obtained from the initial tableau . Furthermore , the same algebraic operations would give these same coefficients even if the values of ...
Page 252
... coefficients of the artificial variables 4 and 6 , the optimal solution for the corresponding dual problem given in Table 6.15 is read from the coefficients of x3 , X4 , and x6 as ( y1 , Y2 , y ) = ( 0.5 , 1.1 , 0 ) . As usual , the ...
... coefficients of the artificial variables 4 and 6 , the optimal solution for the corresponding dual problem given in Table 6.15 is read from the coefficients of x3 , X4 , and x6 as ( y1 , Y2 , y ) = ( 0.5 , 1.1 , 0 ) . As usual , the ...
Page 274
... Coefficients of a Basic Variable Now suppose that the variable x ; ( fixed j ) under consideration is a basic variable in the optimal solution shown by the final simplex tableau . Case 3 assumes that the only changes in the current ...
... Coefficients of a Basic Variable Now suppose that the variable x ; ( fixed j ) under consideration is a basic variable in the optimal solution shown by the final simplex tableau . Case 3 assumes that the only changes in the current ...
Other editions - View all
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 Courseware CPLEX decision variables dual problem dual simplex method dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal programming graphical identify increase initial BF solution integer 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 resource right-hand sides sensitivity analysis shadow prices shown slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero