Every morning at 9:30am, the manager of a fast-food restaurant determines how many hamburgers to pre-make so they are ready to be immediately given to customers at lunchtime. If not enough are pre-made, customers will have to wait a long time in line, and might go to the competing fast-food restaurant next door instead. If too many are pre-made, some will spoil before they canbe used

The manager has come up with another incorrect idea: GIVEN past data on the probability _pkn that hamburgers will be ordered at lunch today if were ordered yesterday, USE a Markov chain model TO find the steady-state probabilities _k that there are k hamburgers ordered at lunch in a day. Then, Given those probabilities and the relative costs of losing customers or having hamburgers spoil, USE an optimization model TO determine the most cost-effective number of hamburgers to order each day.

Select all of the statements below that show a reason why the manager's idea is wrong.

a.The Markov chain model can't link one day to the next.

b.The Markov chain model doesn't account for seasonality

c.The Markov chain model doesn't account for attributes of days (holidays, etc.).

d.The number of hamburgers sold day to day isn't memoryless.