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 174
Reconsider the model in Prob . 4.1-5 . Follow the instructions of Prob . 4.2-1 for parts ( a ) , ( b ) , and ( c ) . ( d ) Repeat part ( b ) for the corner - point infeasible solutions and the corresponding basic infeasible solutions .
Reconsider the model in Prob . 4.1-5 . Follow the instructions of Prob . 4.2-1 for parts ( a ) , ( b ) , and ( c ) . ( d ) Repeat part ( b ) for the corner - point infeasible solutions and the corresponding basic infeasible solutions .
Page 289
Consider the model of Prob . 6.7-1 . Use duality theory directly to determine whether the current basic solution remains optimal after each of the following independent changes . ( a ) The change in part ( e ) of Prob .
Consider the model of Prob . 6.7-1 . Use duality theory directly to determine whether the current basic solution remains optimal after each of the following independent changes . ( a ) The change in part ( e ) of Prob .
Page 1082
Use the policy improvement algorithm to find an optimal policy for Prob . ... in Prob . 16.6-5 . Suppose now that the number of pints of blood delivered ( on a regular delivery ) can be specified at the time of delivery ( instead of ...
Use the policy improvement algorithm to find an optimal policy for Prob . ... in Prob . 16.6-5 . Suppose now that the number of pints of blood delivered ( on a regular delivery ) can be specified at the time of delivery ( instead of ...
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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 assignment basic solution basic variable BF solution bound boundary called changes coefficients column complete Consider constraints Construct corresponding cost CPF solution decision variables demand described determine direction distribution dual problem entering equal equations estimates example feasible feasible region FIGURE final flow formulation 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 remaining resource respective resulting shown shows side simplex method simplex tableau slack solve step supply Table tableau tion unit weeks Wyndor Glass zero