Question: answer 16, 17 & 18 Chapter 12 , problem 39 Burger Prince buys top-grade ground beef for $1.00 per pound. A large sign over the

answer 16, 17 & 18
answer 16, 17 & 18 Chapter 12 , problem 39 Burger
answer 16, 17 & 18 Chapter 12 , problem 39 Burger
Chapter 12 , problem 39 Burger Prince buys top-grade ground beef for $1.00 per pound. A large sign over the entrance guarantees that the meat is fresh daily. Any leftover meat is sold to the local high school cafeteria for 80 cents per pound. Four hamburgers can be prepared from each pound of meat. Burgers sell for 60 cents each. Labor, overhad, meat, bun and condiments cost 50 cents per burger. Demand is normally distributed with a mean of 400 pounds per day and a standard deviation of 50 pounds per day. What is the possible profit and loss for 1 pound of ground beef? $2.40,$1.00 $1.40,$0.20 $0.60,$0.20 $0.40,$0.20 Chapter 12 , Problem 39 Burger Prince buys top-grade ground beef for $1.00 per pound. A large sign over the entrance guarantees that the meat is fresh daily. Any leftover meat is sold to the local high school cafeteria for 80 cents per pound. Four hamburgers can be prepared from each pound of meat. Burgers sell for 60 cents each. Labor, overhead, meat, buns, and condiments cost 50 cents per burger. Demand is normally distributed with a mean of 400 pounds per day and a standard deviation of 50 pounds per day. What is the optimal service level for this problem? (Please keep 4 digits after the decimal point.) QUESTION 18 Chapter 12, Problem 39 Burger Prince buys top-grade ground beef for $1.00 per pound. A large sign over the entrance guarantees that the meat is fresh daily. Any leftover meat is sold to the local high school cafeteria for 80 cents per pound. Four hamburgers can be prepared from each pound of meat. Burgers sell for 60 cents each. Labor, overhead, meat, buns, and condiments cost 50 cents per burger. Demand is normally distributed with a mean of 400 pounds per day and a standard deviation of 50 pounds per day. What daily order quantity is optimal

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