Consider the following inventory problem. A camera store stocks a rticular model camera that can be ordered weekly. Let D1, D2, . . . represent e demand for this camera (the number of units that would be sold if the ventory is not depleted) during the first week, second week
Consider the following inventory problem. A camera store stocks a rticular model camera that can be ordered weekly. Let D1, D2, . . . represent e demand for this camera (the number of units that would be sold if the ventory is not depleted) during the first week, second week
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![5. Consider the following inventory problem. A camera store stocks a
Particular model camera that can be ordered weekly. Let D1, D2, . . represent
the demand for this camera (the number of units that would be sold if the
inventory is not depleted) during the first week, second week, ..
respectively. It is assumed that the D; are independent and identically
distributed random variables having a Poisson distribution with a mean of 1.5.
Let Xo represent the number of cameras on hand at the outset, X1 the number
of cameras on hand at the end of week 1, X2 the number of cameras on hand
at the end of week 2, and so on. Assume that Xo = 3. On Saturday night the
store places an order that is delivered in time for the next opening of the store
on Monday. The store uses the following order policy: If there are no cameras
in stock, the store orders 3 cameras. However, if there are any cameras in
stock, no order is placed. Sales are lost when demand exceeds the inventory
on hand. Thus, {Xt} for t = 0, 1, ... is a stochastic process of the form just
described. The possible states of the process are the integers 0, 1, 2, 3,
representing the possible number of cameras on hand at the end of the week.
The random variables X; are dependent and may be evaluated iteratively by
the expression
max{3 – Dt+1 , 0} if X; = 0
таx{x, — De+1 , 0} if X, 2 1
X++1
for t=0,1,2,...
7
(a) evaluate the various transition probabilities
EV [ 10]
(b) Obtain the transition matrix for the above problem.
CR [ 10]](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F1810b466-a551-4741-a06b-ee294dafc91b%2Fd9384b21-2ea6-4af5-9ef7-af15f69fef73%2Ftpl3cfh_processed.png&w=3840&q=75)
Transcribed Image Text:5. Consider the following inventory problem. A camera store stocks a
Particular model camera that can be ordered weekly. Let D1, D2, . . represent
the demand for this camera (the number of units that would be sold if the
inventory is not depleted) during the first week, second week, ..
respectively. It is assumed that the D; are independent and identically
distributed random variables having a Poisson distribution with a mean of 1.5.
Let Xo represent the number of cameras on hand at the outset, X1 the number
of cameras on hand at the end of week 1, X2 the number of cameras on hand
at the end of week 2, and so on. Assume that Xo = 3. On Saturday night the
store places an order that is delivered in time for the next opening of the store
on Monday. The store uses the following order policy: If there are no cameras
in stock, the store orders 3 cameras. However, if there are any cameras in
stock, no order is placed. Sales are lost when demand exceeds the inventory
on hand. Thus, {Xt} for t = 0, 1, ... is a stochastic process of the form just
described. The possible states of the process are the integers 0, 1, 2, 3,
representing the possible number of cameras on hand at the end of the week.
The random variables X; are dependent and may be evaluated iteratively by
the expression
max{3 – Dt+1 , 0} if X; = 0
таx{x, — De+1 , 0} if X, 2 1
X++1
for t=0,1,2,...
7
(a) evaluate the various transition probabilities
EV [ 10]
(b) Obtain the transition matrix for the above problem.
CR [ 10]
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