Chapter Four: Linear Programming: Modeling Examples

← Back to document page

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 (ma)

Data envelopment analysis 49. Data envelopment analysis 50. Network flow (maximization) 51. Multiperiod workforce planning (minimization) 52. Integer solution (4–43) 53. Machine scheduling (maximization), sensitivity analysis 54. Cargo storage (maximization) 55. Broadcast scheduling (maximization) 56. Product mix (maximization) 57.

  Analysis, Data, Data envelopment analysis, Envelopment