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 382
... machines of different types . There are four available locations in the shop where a machine could be installed . Some of these locations are more desirable than others for particular machines because of their proxim- ity to work ...
... machines of different types . There are four available locations in the shop where a machine could be installed . Some of these locations are more desirable than others for particular machines because of their proxim- ity to work ...
Page 832
... machine that , when operational at the beginning of a day , has a probability of 0.1 of breaking down sometime during the day . When this happens , the repair is done the next day and completed at the end of that day . ( a ) Formulate ...
... machine that , when operational at the beginning of a day , has a probability of 0.1 of breaking down sometime during the day . When this happens , the repair is done the next day and completed at the end of that day . ( a ) Formulate ...
Page 900
... machines . For each machine , the probability distribution of the run- ning time before a breakdown is exponential , with a mean of 9 hours . The repair time also has an exponential distribution , with a mean of 2 hours . ( a ) Which ...
... machines . For each machine , the probability distribution of the run- ning time before a breakdown is exponential , with a mean of 9 hours . The repair time also has an exponential distribution , with a mean of 2 hours . ( a ) Which ...
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