Question: I would like you to use the data file provided, which contains information on 109 2019 sets that had positive value potentials from the themes

I would like you to use the data file provided, which contains information on 109 2019 sets that had positive value potentials from the themes I discuss in the (B) version of the case. Your task is to build an optimization model that determines which sets to invest in and how many of each to buy to maximize the total value potential while meeting the other conditions described in the case. I would like you to build and solve the model using the $4,000 budget figure given in the case. Then I would like you to adjust your model to analyze the range of budget amounts specified in the case and recommend a budget amount for Greg to use based on your analysis.

Below is the case and a screenshot of the excel page. Please show me how to do this, will thumbs up. Thank you!

Case:

While the future value of a retired LEGO set is partially dependent upon the desirability of the set itself as well as the theme (such as Harry Potter, Minecraft, Star Wars, etc.), another major determinant of the desirability of a set as an investment is the value potential, which is defined as the difference between the price that LEGO should be charging for the set based on its characteristics and the actual retail price. Sets with large value potential represent outsized investment opportunities in much the same way that a value mutual fund invests in securities that are potentially undervalued based on their fundamentals.

In his prior analysis Greg has developed a model that determines the price that LEGO should be charging for sets and has used it to determine the value potential for all of the sets that were released in 2019. Some sets ending up having positive value potentials, while others had negative value potentials. He eliminated all of the sets with negative value potential from further investment consideration. He also researched the resale prices for retired LEGO sets on the secondary market and narrowed his potential investment options to sets in the following themes: City, Creator, DC Super Heroes, Friends, Harry Potter, Hidden Side, Ideas, Marvel Super Heroes, Minecraft, Ninjago, Overwatch, Speed Champions, and Star Wars. This left him with the 109 sets listed in the data file provided.

Gregs task now is to determine which specific sets he should purchase as an investment. He has initially allocated $4,000 to his investment budget, although he is open to adjusting that amount up or down within the range from $2,000 to $6,000 based on the relationship between value potential and total investment.

Like any well-constructed investment portfolio, Greg also wants to ensure that he is properly diversified to limit his exposure to adverse market conditions affecting one particular set or theme in the future. As a result, he had decided not to purchase more than 10 copies of any one set, and he seeks to avoid any one theme representing more than 20% of the total number of LEGO sets that he has purchased.

Based on his analysis of sets selling on the secondary market, however, Greg thinks that sets from three themesHidden Side, Ideas, and Star Warshave the potential to increase in value significantly upon retirement; and he wants to be in position to take advantage of such an opportunity in the future. Therefore, he requires that at least 5% of the total sets purchased are from each of those three themes.

Perhaps most importantly, Greg wants to avoid the wrath of his wife, who is not interested in turning their entire house into a warehouse for his new investments to sit while they appreciate. He has negotiated the use of one metal shelving unit with dimensions 60 inches x 36 inches x 24 inches that is set up in the basement to store these LEGO sets. He has assured his wife that the sets he purchases for investment will fit entirely on those shelves.

Excel:

I would like you to use the data file provided,

B D D E F G H K L M 1 Theme 2 Subtheme Sky Police Fire Fire 3 4 4 Value Potential 3.55 2.93 7.96 4.42 4.28 2.50 4.11 5 6 7 City City City City City City City City City City City City Juniors 8 9 10 11 7.06 11.88 4.25 6.45 4.08 Space Space Sky Police 12 13 14 4.02 15 5.67 16 Set # Name 2019 60206 Jet Patrol 2019 60212 Barbecue Burn Out 2019 60216 Downtown Fire Brigade 2019 60218 Desert Rally Racer 2019 60219 Construction Loader 2019 60220 Garbage Truck 2019 60221 Diving Yacht 2019 60222 Snow Groomer 2019 60223 Harvester Transport 2019 60224 Satellite Service Mission 2019 60228 Deep Space Rocket and Launch Control 2019 60239 Police Patrol Car 2019 60240 Kayak Adventure 2019 31086 Futuristic Flyer 2019 31087 Dune Buggy 2019 31088 Deep Sea Creatures 2019 31089 Sunset Track Racer 2019 31090 Underwater Robot 2019 31091 Shuttle Transporter 2019 31092 Helicopter Adventure 2019 31093 Riverside Houseboat 2019 31094 Race Plane 2019 31095 Fairground Carousel 2019 31096 Twin-Rotor Helicopter 2019 31097 Townhouse Pet Shop & Caf 2019 31098 Outback Cabin 2019 76116 Batman Batsub and the Underwater Clash 2019 76118 Mr. Freeze Batcycle Battle 2019 76119 Batmobile: Pursuit of the Joker Release Month (US) Piece Count Weight (lb.) Volume (cu in) US Retail Price ($) Estimated Retail Price January 54 0.32 81.84 9.99 13.54482315 January 64 0.29 61.38 9.99 12.91864522 January 943 4.06 985.635 99.99 107.9500931 January 75 0.35 81.84 9.99 14.40820776 January 88 0.34 81.84 9.99 14.27344945 January 90 0.69 185.4 19.99 22.48687562 January 148 0.74 185.4 19.99 24.101842 January 197 0.85 185.4 19.99 27.05333436 January 358 1.43 364.875 29.99 41.87073883 June 84 0.34 81.84 9.99 14.24284214 June 837 4.03 496.125 99.99 106.4363031 January 92 0.33 61.38 9.99 14.06982469 January 84 0.33 61.38 9.99 14.00861006 January 157 0.59 109.592 14.99 20.65722737 January 147 0.55 100.8 12.99 19.64378081 January 230 0.68 109.592 14.99 23.32389946 January 221 0.84 185.4 19.99 27.00274616 January 207 0.79 185.4 19.99 25.72446021 January 341 1.12 239.775 24.99 34.47946353 January 114 0.42 75.6 16.34625355 January 396 1.48 291.9 39.99 43.33266866 January 333 1.41 291.9 29.99 41.21097899 August 595 2.60 503.496 49.99 71.08937447 August 569 3.20 608.391 59.99 84.94435125 August 969 3.74 714.714 79.99 100.6536143 August 305 1.19 232.65 29.99 35.84362223 January 174 0.70 185.4 19.99 23.36386124 July 200 0.66 185.4 19.99 22.62588048 August 342 1.15 291.9 29.99 35.18981157 17 18 6.65 8.33 7.01 5.73 9.49 19 20 21 9.99 City Creator Creator Creator Creator Creator Creator Creator Creator Creator Creator Creator Creator Creator DC Super Heroes DC Super Heroes DC Super Heroes 22 23 24 6.36 3.34 11.22 21.10 24.95 20.66 5.85 25 26 27 28 3.37 29 Batman Batman Batman 2.64 5.20 30 21 no

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