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. |
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Page 177
( d ) For objective functions where this model has no optimal solu- tion , does this mean that there are no good solutions accord- ing to the model ? Explain . What probably went wrong when formulating the model ?
( d ) For objective functions where this model has no optimal solu- tion , does this mean that there are no good solutions accord- ing to the model ? Explain . What probably went wrong when formulating the model ?
Page 273
Cj Analyzing Simultaneous Changes in Objective Function Coefficients . Regard- less of whether x , is a basic or nonbasic variable , the allowable range to stay optimal for c ; is valid only if this objective function coefficient is the ...
Cj Analyzing Simultaneous Changes in Objective Function Coefficients . Regard- less of whether x , is a basic or nonbasic variable , the allowable range to stay optimal for c ; is valid only if this objective function coefficient is the ...
Page 596
Yij + Note that the first three functional constraints ensure that each x ; will be assigned just one of its possible values . ( Here yi Yi2 + Yi3 = 0 corresponds to x = 0 , which con- tributes nothing to the objective function . ) ...
Yij + Note that the first three functional constraints ensure that each x ; will be assigned just one of its possible values . ( Here yi Yi2 + Yi3 = 0 corresponds to x = 0 , which con- tributes nothing to the objective function . ) ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity additional algorithm allowable amount apply assigned basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider Construct corresponding cost CPF solution decision variables described determine developed dual problem entering equations estimates example feasible feasible region feasible solutions FIGURE final flow formulation functional constraints given gives goal identify illustrate increase indicates initial iteration linear programming linear programming model Maximize million Minimize month needed node objective function obtained operations optimal optimal solution original parameters path perform plant possible presented primal problem Prob procedure profit programming problem provides range resource respective resulting revised sensitivity analysis shown shows side simplex method simplex tableau slack solve step Table tableau tion unit values weeks Wyndor Glass x₁ zero