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
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Page 15
... parameters of the model are most critical ( the " sensitive parameters " ) in deter- mining the solution . A common definition of sensitive parameter ( used throughout this book ) is the following . For a mathematical model with ...
... parameters of the model are most critical ( the " sensitive parameters " ) in deter- mining the solution . A common definition of sensitive parameter ( used throughout this book ) is the following . For a mathematical model with ...
Page 156
... parameters ( i.e. , those that cannot be changed without changing the optimal solution ) . The sensitive parameters are the parameters that need to be estimated with special care to minimize the risk of ob- taining an erroneous optimal ...
... parameters ( i.e. , those that cannot be changed without changing the optimal solution ) . The sensitive parameters are the parameters that need to be estimated with special care to minimize the risk of ob- taining an erroneous optimal ...
Page 255
... parameters take on other possible values . Usually there will be some parameters that can be assigned any rea- sonable value without the optimality of this solution being affected . However , there may also be parameters with likely ...
... parameters take on other possible values . Usually there will be some parameters that can be assigned any rea- sonable value without the optimality of this solution being affected . However , there may also be parameters with likely ...
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 dual problem dual simplex method dynamic programming entering basic variable estimates example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal programming 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 slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion unit profit values weeks Wyndor Glass x₁ zero