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 838
... waiting line need not be people . For example , they may be items waiting for a certain operation by a given type of machine , or they may be cars waiting in front of a tollbooth . It is not necessary that there actually be a physical ...
... waiting line need not be people . For example , they may be items waiting for a certain operation by a given type of machine , or they may be cars waiting in front of a tollbooth . It is not necessary that there actually be a physical ...
Page 911
... waiting times , it is necessary to adopt ( explicitly or implicitly ) a common measure of their impact . The natural choice for this common measure is cost , which then requires estima- tion of the cost of waiting . Because of the ...
... waiting times , it is necessary to adopt ( explicitly or implicitly ) a common measure of their impact . The natural choice for this common measure is cost , which then requires estima- tion of the cost of waiting . Because of the ...
Page 912
... waiting E ( WC ) Solution Level of service 18.3 is being wasted by this idleness is productive output , in which case the waiting cost be- comes the lost profit from all lost productivity . Given that the cost of waiting has been ...
... waiting E ( WC ) Solution Level of service 18.3 is being wasted by this idleness is productive output , in which case the waiting cost be- comes the lost profit from all lost productivity . Given that the cost of waiting has been ...
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