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. |
From inside the book
Results 1-3 of 72
Page 744
... determine which strategy the respective manufacturers should use according to the minimax criterion . 14.1-3 . Consider the following parlor game to be played between two players . Each player begins with three chips : one red , one ...
... determine which strategy the respective manufacturers should use according to the minimax criterion . 14.1-3 . Consider the following parlor game to be played between two players . Each player begins with three chips : one red , one ...
Page 829
... determine the n - step transition matrix P ( " ) for n = € 5 , 10 , 20 , 40 , 80 . c ( c ) Use your OR Courseware to determine the steady - state prob- abilities of the state of the Markov chain . Describe how the probabilities in the n ...
... determine the n - step transition matrix P ( " ) for n = € 5 , 10 , 20 , 40 , 80 . c ( c ) Use your OR Courseware to determine the steady - state prob- abilities of the state of the Markov chain . Describe how the probabilities in the n ...
Page 995
... determine what Freddie's new order quantity should be to maximize his expected daily profit . ( b ) Apply Bayes ' decision rule again , but this time with the crite- rion of minimizing Freddie's expected daily cost of under- ordering or ...
... determine what Freddie's new order quantity should be to maximize his expected daily profit . ( b ) Apply Bayes ' decision rule again , but this time with the crite- rion of minimizing Freddie's expected daily cost of under- ordering or ...
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