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 174
Reconsider the model in Prob . 4.1-4 . ( a ) Introduce slack variables in order to write the functional con- straints in augmented form . ( b ) For each CPF solution , identify the corresponding BF solution by calculating the values of ...
Reconsider the model in Prob . 4.1-4 . ( a ) Introduce slack variables in order to write the functional con- straints in augmented form . ( b ) For each CPF solution , identify the corresponding BF solution by calculating the values of ...
Page 289
4.6-3 ( b ) Model in Prob . 4.6-8 ( c ) Model in Prob . 4.6-18 6.4-7 . Consider the model with equality constraints given in Prob . 4.6-2 . ( a ) Construct its dual problem . ( b ) Demonstrate that the answer in part ( a ) is correct ...
4.6-3 ( b ) Model in Prob . 4.6-8 ( c ) Model in Prob . 4.6-18 6.4-7 . Consider the model with equality constraints given in Prob . 4.6-2 . ( a ) Construct its dual problem . ( b ) Demonstrate that the answer in part ( a ) is correct ...
Page 1082
Reconsider Prob . 21.2-4 . ( a ) Formulate a linear programming model for finding an optimal policy . c ( b ) Use the simplex method to solve this model . Use the re- sulting optimal solution to identify an optimal policy . 21.3-5 .
Reconsider Prob . 21.2-4 . ( a ) Formulate a linear programming model for finding an optimal policy . c ( b ) Use the simplex method to solve this model . Use the re- sulting optimal solution to identify an optimal policy . 21.3-5 .
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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