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 40
The conclusion was that proportionality could indeed be assumed without
serious distortion . For other problems , what happens when the proportionality
assumption does not hold even as a reasonable approximation ? In most cases ,
this ...
The conclusion was that proportionality could indeed be assumed without
serious distortion . For other problems , what happens when the proportionality
assumption does not hold even as a reasonable approximation ? In most cases ,
this ...
Page 42
5x1x2 , so the total function value is 6 + 6 + 3 = 15 when ( x1 , x2 ) = ( 2 , 3 ) ,
which violates the additivity assumption that the value is just 6 + 6 = 12 . This
case can arise in exactly the same way as described for Case 2 in Table 3 . 5 ;
namely ...
5x1x2 , so the total function value is 6 + 6 + 3 = 15 when ( x1 , x2 ) = ( 2 , 3 ) ,
which violates the additivity assumption that the value is just 6 + 6 = 12 . This
case can arise in exactly the same way as described for Case 2 in Table 3 . 5 ;
namely ...
Page 43
Certainty Our last assumption concerns the parameters of the model , namely ,
the coefficients in the objective function cj , the ... Certainty assumption : The
value assigned to each parameter of a linear programming model is assumed to
be a ...
Certainty Our last assumption concerns the parameters of the model , namely ,
the coefficients in the objective function cj , the ... Certainty assumption : The
value assigned to each parameter of a linear programming model is assumed to
be a ...
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Contents
SUPPLEMENT TO APPENDIX 3 | 3 |
Problems | 6 |
An Algorithm for the Assignment Problem | 18 |
Copyright | |
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Common terms and phrases
activity additional algorithm allocation allowable amount apply assignment basic solution basic variable BF solution bound boundary calculations called capacity changes coefficients column complete Consider constraints construct corresponding cost CPF solution demand described determine direction distribution dual problem entering equal equations estimates example feasible FIGURE final flow problem Formulate functional constraints given gives goal identify illustrate increase indicates initial iteration linear programming Maximize million Minimize month needed node nonbasic variables objective function obtained operations optimal optimal solution original parameters path plant possible presented primal problem Prob procedure profit programming problem provides range resource respective resulting revised Select shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit values weeks Wyndor Glass zero