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 301
Given 0 , the coefficients of xı in the model become Ci 9 + 907 = ( a ) Construct the resulting revised final tableau ( as a function of 0 ) , and then convert this tableau to proper form from Gaussian elimination .
Given 0 , the coefficients of xı in the model become Ci 9 + 907 = ( a ) Construct the resulting revised final tableau ( as a function of 0 ) , and then convert this tableau to proper form from Gaussian elimination .
Page 791
( c ) Apply the backward induction procedure , and identify the resulting optimal policy . a A 15.4-8 . Jose Morales manages a large outdoor fruit stand in one of the less affluent neighborhoods of San Jose , California .
( c ) Apply the backward induction procedure , and identify the resulting optimal policy . a A 15.4-8 . Jose Morales manages a large outdoor fruit stand in one of the less affluent neighborhoods of San Jose , California .
Page 1082
Use the resulting optimal solution to identify an optimal policy . , 1 21.4-6 . Use the policy improvement algorithm to find an optimal policy for Prob . 21.2-6 . D.1 21.4-7 . Use the policy improvement algorithm to find an optimal ...
Use the resulting optimal solution to identify an optimal policy . , 1 21.4-6 . Use the policy improvement algorithm to find an optimal policy for Prob . 21.2-6 . D.1 21.4-7 . Use the policy improvement algorithm to find 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 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