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 215
What this portion of the tableau reveals is how the entire final tableau ( except row 0 ) has been obtained from the initial tableau , namely , ( } ) ( initial row 2 ) + ( ) ( initial row 2 ) + ( − ) ( initial row 2 ) + ...
What this portion of the tableau reveals is how the entire final tableau ( except row 0 ) has been obtained from the initial tableau , namely , ( } ) ( initial row 2 ) + ( ) ( initial row 2 ) + ( − ) ( initial row 2 ) + ...
Page 216
Even when the simplex method has gone through hundreds or thousands of iterations , the coefficients of the slack vari- ables in the final tableau will reveal how this tableau has been obtained from the initial tableau .
Even when the simplex method has gone through hundreds or thousands of iterations , the coefficients of the slack vari- ables in the final tableau will reveal how this tableau has been obtained from the initial tableau .
Page 397
D. ( b ) Use the northwest corner rule to obtain an initial BF solu- tion for this problem . DI ( c ) Starting with the initial BF solution from part ( b ) , interac- tively apply the transportation simplex method to obtain an optimal ...
D. ( b ) Use the northwest corner rule to obtain an initial BF solu- tion for this problem . DI ( c ) Starting with the initial BF solution from part ( b ) , interac- tively apply the transportation simplex method to obtain an optimal ...
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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