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. |
From inside the book
Results 1-3 of 95
Page 294
After further negotiations with each vendor , management of the G. A. Tanner Co. has learned that either of them would be willing to consider increasing their supply of their respective subassemblies over the previously stated maxima ...
After further negotiations with each vendor , management of the G. A. Tanner Co. has learned that either of them would be willing to consider increasing their supply of their respective subassemblies over the previously stated maxima ...
Page 364
s production scheduling problem , where there was excess supply capacity . Now there is excess demand capacity . Consequently , rather than introducing a dummy destination to “ receive " the unused supply capacity , the adjustment ...
s production scheduling problem , where there was excess supply capacity . Now there is excess demand capacity . Consequently , rather than introducing a dummy destination to “ receive " the unused supply capacity , the adjustment ...
Page 986
In 1989 , SPAM began bringing supply chain management concepts into HP . HP's supply chain includes manufacturing integrated circuits , board assembly , final assembly , and delivery to customers on a global basis .
In 1989 , SPAM began bringing supply chain management concepts into HP . HP's supply chain includes manufacturing integrated circuits , board assembly , final assembly , and delivery to customers on a global basis .
What people are saying - Write a review
We haven't found any reviews in the usual places.
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 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