- A convenience store needs to make a decision of how many packages of California rolls prepare for tomorrow. A package of California rolls cost the store $2.00 and it sells for $6.00. Daily demand is normally distributed with a mean of 100 packages of California rolls and a standard deviation of 40 packages of California rolls. If there are leftovers at the end of the day, the store donates them.
- Use simulation optimization to find the optimal packages of California rolls that maximizes the store’s profit.
- Add a chance constraint to the model (VaR constraint) to make sure that there is a 90% chance that California rolls are available to the customers. Then, use optimization to find the optimal packages of California rolls that maximizes the store’s profit.
2.Marcy Hotel is a boutique hotel in Boston downtown area. The operations manager, Jenna, needs your help to decide how many rooms (of a particular type) to book for a day. The nightly stay in these rooms is $200 and the hotel has 100 of those rooms. The data shows that some customers do not show-up. To protect against no show-ups, Jenna is considering to book more than 100 rooms per night. Although this practice allows Jenna to utilize each room available as much as possible, it comes with a risk. The risk is that if Jenna books more than 100 rooms and if more customers than expected show-up, then some customers will not be able to stay at the hotel even though they made a reservation. To protect those customers, Marcy Hotel is providing a compensation of 120% of the booking price paid by the customer. Also, any no show-up customer Is refunded 30% of the booking price paid by the customer. How many rooms should Jane book in a day to maximize its expected revenue. Answer this question by developing a simulation optimization model. In your model, assume that the number of no-shows is lognormally distributed with a mean of (0.2*number of rooms booked) and standard deviation of (0.05*number of rooms booked).
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