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. |
From inside the book
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Page 74
This corporation has 10 plants in various parts of the world . Each of these plants produces the same 10 products and then sells them within its region . The de- mand ( sales potential ) for each of these products from each plant is ...
This corporation has 10 plants in various parts of the world . Each of these plants produces the same 10 products and then sells them within its region . The de- mand ( sales potential ) for each of these products from each plant is ...
Page 103
One plant outside Detroit , MI , assembles two models from the family of midsized and luxury cars . The first model , the Family Thrillseeker , is a four - door sedan with vinyl seats , plastic interior , standard features ...
One plant outside Detroit , MI , assembles two models from the family of midsized and luxury cars . The first model , the Family Thrillseeker , is a four - door sedan with vinyl seats , plastic interior , standard features ...
Page 388
There are more products ( four ) than plants ( three ) , so one of the plants will need to be assigned two products . Plant 3 has only enough excess capacity to produce one prod- uct ( see Table 8.27 ) , so either Plant 1 or Plant 2 ...
There are more products ( four ) than plants ( three ) , so one of the plants will need to be assigned two products . Plant 3 has only enough excess capacity to produce one prod- uct ( see Table 8.27 ) , so either Plant 1 or Plant 2 ...
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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