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Chapter Four: Linear Programming: Modeling Examples

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40PROBLEM SUMMARY1. Product mix example2. Diet example3. Investment example4. Marketing example5. Transportation example6. Blend mix (maximization) analysis (4 7) (minimization) mix (minimization) mix (maximization) mix (maximization) mix (maximization) mix (minimization) (maximization) mix (maximization) mix (minimization) distribution (maximization) allocation (maximization) (minimization), sensitivity (maximization) (minimization) scheduling (minimization) busing (minimization) analysis (4 24) mixture (minimization) scheduling (maximization) mixture (maximization) poly mix (maximization) mix (maximization) mix (minimization), sensitivity analysisChapter Four: Linear Programming: Modeling (maximization) borrowing (minimization) production scheduling(minimization) (maximization), sensitivity (minimization), sensitivity (minimization) (minimization) line scheduling (maximization) flow (minimization) admissions (maximization) (maximization) loss (minimization) investment (maximization) sales and inventory (maximization) production and inventory(minimization) assignment (maximization) envelo

Many different combinations of maximum servings of each of the 10 food items could be used. As an example limiting the four hot and cold cereals, x1, x2, x3 and x4 to four cups, eggs to three, bacon to three slices, oranges to two, milk to two cups, orange juice to four cups and wheat toast to four slices results in the following solution: x3 ...

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