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 91
They earn $ 60 profit for each wood - framed window and $ 30 profit for each aluminum - framed window . Doug makes the wood frames , and can make 6 per day . Linda makes the aluminum frames , and can make 4 per day .
They earn $ 60 profit for each wood - framed window and $ 30 profit for each aluminum - framed window . Doug makes the wood frames , and can make 6 per day . Linda makes the aluminum frames , and can make 4 per day .
Page 297
( a ) What is the optimal solution and total profit ? ( b ) Suppose the profit per gallon of banana changes to $ 1.00 . Will the optimal solution change , and what can be said about the effect on total profit ? ( c ) Suppose the profit ...
( a ) What is the optimal solution and total profit ? ( b ) Suppose the profit per gallon of banana changes to $ 1.00 . Will the optimal solution change , and what can be said about the effect on total profit ? ( c ) Suppose the profit ...
Page 297
( a ) What is the optimal solution and total profit ? ( b ) Suppose the profit per gallon of banana changes to $ 1.00 . Will the optimal solution change , and what can be said about the effect on total profit ? ( c ) Suppose the profit ...
( a ) What is the optimal solution and total profit ? ( b ) Suppose the profit per gallon of banana changes to $ 1.00 . Will the optimal solution change , and what can be said about the effect on total profit ? ( c ) Suppose the profit ...
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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