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Model 4: The Nut Company and the Simplex Method

Model 4: The Nut Company and the Simplex Method. AJ Epel Thursday, Oct. 1. Contents. The Problem Assumptions and Constraints The Linear Program Step-by-step Review: Simplex Method Solution by Computer Conclusion. The Problem. Three different blends for sale Regular - sells for $0.59/lb

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Model 4: The Nut Company and the Simplex Method

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  1. Model 4: The Nut Companyand the Simplex Method AJ Epel Thursday, Oct. 1

  2. Contents • The Problem • Assumptions and Constraints • The Linear Program • Step-by-step Review: Simplex Method • Solution by Computer • Conclusion

  3. The Problem • Three different blends for sale • Regular - sells for $0.59/lb • Deluxe - sells for $0.69/lb • Blue Ribbon - sells for $0.85/lb • Four kinds of nuts can be mixed in each • Almonds - costs $0.25/lb • Pecans - costs $0.35/lb • Cashews - costs $0.50/lb • Walnuts - costs $0.30/lb

  4. The Problem • How should the company maximize weekly profit? • What amounts of each nut type should go into each blend? • Use a linear model!

  5. Assumptions and Constraints • Non-negative quantities of nuts and blends • Continuous model: fractions okay • Costs, quantities supplied constant from week to week • Can sell all blends made at their listed selling prices • Not every nut needs to be in each blend

  6. Assumptions and Constraints • Max. quantities of supplied nuts • Almonds: 2000 lbs. altogether • Pecans: 4000 lbs. altogether • Cashews: 5000 lbs. altogether • Walnuts: 3000 lbs. altogether

  7. Assumptions and Constraints • Proportions of one nut to the whole blend • Regular • No more than 20% cashews • No more than 25% pecans • No less than 40% walnuts • Deluxe • No more than 35% cashews • No less than 25% almonds • Blue Ribbon • No more than 50% cashews • No less than 30% cashews • No less than 30% almonds

  8. The Linear Program • Let Xjk = quantity of nut type j in blend k • Let Mjk = margin for nut type j in blend k • Let π = profit to company • So π = for k = 1...3for j = 1...4 (MjkXjk)

  9. The Linear Program • On future slides, Xjk may be written as Jk • J is the nut type: A(lmond), P(ecan), C(ashew), W(alnut) • k is the blend: r(egular), d(eluxe), b(lue ribbon)

  10. The Linear Program • Quantity constraints • for j = 1...4Xjk ≤ Max. quantity. for j • Example: Ar + Ad + Ab ≤ 2000 • Proportion constraints • Example: Cr ≤ 0.2(Ar + Pr + Cr + Wr) • 0.8Cr - 0.2Ar - 0.2Pr - 0.2Wr ≤ 0 • “No less than” constraints • Multiply everything by -1

  11. The Linear Program • Max π = .34Ar + .44Ad + .6Ab + .24Pr + .34Pd + .5Pb + .09Cr + .19Cd + .35Cb +.29Wr +.39Wd + .55Wb subject to • Ar + Ad + Ab ≤ 2000 • Pr + Pd + Pb ≤ 4000 • Cr + Cd + Cb ≤ 5000 • Wr + Wd + Wb ≤ 3000 • -.2Ar - .2Pr + .8Cr - .2Wr ≤ 0 • -.25Ar + .75Pr - .25Cr - .25Wr ≤ 0 • -.35Ad - .35Pd + .65Cd - .35Wd ≤ 0 • -.5Ab - .5Pb + .5Cb - .5Wb ≤ 0 • .4Ar + .4Pr + .4Cr - .6Wr ≤ 0 • -.75Ad + .25Pd + .25Cd + .25Wd ≤ 0 • .3Ab + .3Pb - .7Cb + .3Wb ≤ 0 • -.7Ab + .3Pb + .3Cb + .3Wb ≤ 0

  12. The Tableau: Setup

  13. Step 1 and Step 2

  14. Step 3 and Step 4

  15. Solution by Computer

  16. Conclusion • Maximum weekly profit: $4524.24 • Buy these: • Almonds: 2000 lbs. • Pecans: 4000 lbs. • Cashews: 3121 lbs. • Walnuts: 3000 lbs.

  17. Conclusion • Blend 5455 lbs. of Regular this way: • 1364 lbs. pecan (25% of blend) • 1091 lbs. cashew (20% of blend) • 3000 lbs. walnut (55% of blend) • Eliminate Deluxe blend • Blend 6667 lbs. of Blue Ribbon this way: • 2000 lbs. almond (30% of blend) • 2636 lbs. pecan (39.55% of blend) • 2030 lbs. cashew (30.45% of blend)

  18. Conclusion: What if Deluxe can’t be eliminated? • New constraints: • Ar + Pr + Cr + Wr ≥ 1 lb. • Ad + Pd + Cd + Wd ≥ 1 lb. • Ab + Pb + Cb + Wb ≥ 1 lb. • Solved again • Profit = $4524.14 ($0.10/week less) • Only 1 lb. of Deluxe manufactured! • 75% pecan, 25% almond • 1 less lb. of Blue Ribbon

  19. Sources used on the Simplex method • Shepperd, Mike. "Mathematics C: linear programming: simplex method.” July 2003. <http://www.teachers.ash.org.au/miKemath/mathsc/linearprogramming/simplex.PDF> • Reveliotis, Spyros. “An introduction to linear programming and the simplex algorithm.” 20 June 1997. <http://www2.isye.gatech.edu/~spyros/LP/LP.html> • Waner, Stefan and Steven R. Costenoble. “Tutorial for the simplex method.” May 2000. <http://people.hofstra.edu/Stefan_Waner/RealWorld/tutorialsf4/frames4_3.html>

  20. Questions?

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