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 1
... demand studies since the 1938 work of Schultz ( 31 ) 1 were partial demand analyses , in which a food price and per capita income were considered as major determinant variables in a demand equation , but they did not consider the ...
... demand studies since the 1938 work of Schultz ( 31 ) 1 were partial demand analyses , in which a food price and per capita income were considered as major determinant variables in a demand equation , but they did not consider the ...
Page
... demand places us. All of his words speak about the one demand, but not with as much as a single syllable does he break its silence. What his proclamation does say about the demand is that it is God's demand. And because it is God's ...
... demand places us. All of his words speak about the one demand, but not with as much as a single syllable does he break its silence. What his proclamation does say about the demand is that it is God's demand. And because it is God's ...
Page 256
... demand as of early 1993. This will be followed in Section II by an evaluation of the current state of telecommunications demand analysis and list the areas which in my view are in need of continued or expanded research . Some final ...
... demand as of early 1993. This will be followed in Section II by an evaluation of the current state of telecommunications demand analysis and list the areas which in my view are in need of continued or expanded research . Some final ...
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