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 9
... needed both to gain an accurate understanding of the problem and to provide the needed input for the mathematical model being formu- lated in the next phase of study . Frequently , much of the needed data will not be available when the ...
... needed both to gain an accurate understanding of the problem and to provide the needed input for the mathematical model being formu- lated in the next phase of study . Frequently , much of the needed data will not be available when the ...
Page 530
... needed to print and package the application materials and the time needed for the materials to reach the companies . ) 2 days ( This figure includes the time needed to print and package the application materials ) . * An open interview ...
... needed to print and package the application materials and the time needed for the materials to reach the companies . ) 2 days ( This figure includes the time needed to print and package the application materials ) . * An open interview ...
Page 984
... needed between the inventories of any particular product at the dif- ferent echelons . Since the inventory at each echelon ( except the top one ) is replenished from the next higher echelon , the inventory level currently needed at the ...
... needed between the inventories of any particular product at the dif- ferent echelons . Since the inventory at each echelon ( except the top one ) is replenished from the next higher echelon , the inventory level currently needed at the ...
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 CPF solution CPLEX decision variables described 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 graphical identify increase initial BF solution integer interior-point 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 right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ zero