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 87
Page 256
... original model would change the numbers in the final sim- plex tableau ( assuming that the same sequence of algebraic operations originally per- formed by the simplex method were to be duplicated ) . Therefore , after making a few sim ...
... original model would change the numbers in the final sim- plex tableau ( assuming that the same sequence of algebraic operations originally per- formed by the simplex method were to be duplicated ) . Therefore , after making a few sim ...
Page 264
... original final simplex tableau ( middle of Table 6.19 ) is that the entries in the right - side column change to the following values : 4 Z * = y * b = [ 0 , 2 , 1 ] 24 = 54 , 18 1 4 6 3 X3 6 b * S * b = 0 0 24 = 12 SO 2 X2 = 12 1 1 0 ...
... original final simplex tableau ( middle of Table 6.19 ) is that the entries in the right - side column change to the following values : 4 Z * = y * b = [ 0 , 2 , 1 ] 24 = 54 , 18 1 4 6 3 X3 6 b * S * b = 0 0 24 = 12 SO 2 X2 = 12 1 1 0 ...
Page 290
... original problem given in part ( d ) . ( f ) Now suppose that the only change in the original problem is that a new variable xnew has been introduced into the model as follows : Maximize Z = 3x1 + x2 + 4x3 + 2x new , subject to and 4y1 ...
... original problem given in part ( d ) . ( f ) Now suppose that the only change in the original problem is that a new variable xnew has been introduced into the model as follows : Maximize Z = 3x1 + x2 + 4x3 + 2x new , subject to and 4y1 ...
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 described 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 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 simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero