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 153
We nearly always have to solve again several times during the model debugging stage ( described in Secs . 2.3 and 2.4 ) , and we usually have to do so a large number of times during the later stages of postoptimality analysis as well .
We nearly always have to solve again several times during the model debugging stage ( described in Secs . 2.3 and 2.4 ) , and we usually have to do so a large number of times during the later stages of postoptimality analysis as well .
Page 254
Other Applications Already we have discussed two other key applications of duality theory to sensitivity analy- sis , namely , shadow prices and the dual simplex method . As described in Secs . 4.7 and 6.2 , the optimal dual solution ...
Other Applications Already we have discussed two other key applications of duality theory to sensitivity analy- sis , namely , shadow prices and the dual simplex method . As described in Secs . 4.7 and 6.2 , the optimal dual solution ...
Page 452
( b ) Use the algorithm described in Sec . 9.3 to solve this shortest- path problem . c ( c ) Formulate and solve a spreadsheet model for this problem . 9.3-6 . The Quick Company has learned that a competitor is plan- ning to come out ...
( b ) Use the algorithm described in Sec . 9.3 to solve this shortest- path problem . c ( c ) Formulate and solve a spreadsheet model for this problem . 9.3-6 . The Quick Company has learned that a competitor is plan- ning to come out ...
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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