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 749
Frederick S. Hillier, Gerald J. Lieberman. 15 Decision Analysis The previous chapters have focused mainly on decision making when the consequences of alternative decisions are known with a reasonable degree of certainty . This decision ...
Frederick S. Hillier, Gerald J. Lieberman. 15 Decision Analysis The previous chapters have focused mainly on decision making when the consequences of alternative decisions are known with a reasonable degree of certainty . This decision ...
Page 750
... decision analysis is whether to make the needed decision immediately or to first do some testing ( at some expense ) to reduce the level of uncertainty about the outcome of the decision . For example , the testing might be field testing ...
... decision analysis is whether to make the needed decision immediately or to first do some testing ( at some expense ) to reduce the level of uncertainty about the outcome of the decision . For example , the testing might be field testing ...
Page 779
... decision tree in representing and solving decision analysis problems . One that has become quite popu- lar is called the influence diagram , and researchers continue to develop others as well.2 Many strategic business decisions are made ...
... decision tree in representing and solving decision analysis problems . One that has become quite popu- lar is called the influence diagram , and researchers continue to develop others as well.2 Many strategic business decisions are made ...
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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