M/M/1 Queue System: Calculating A, B, C

In summary: For a customer named John Smith, what is the probability he spends > 10 min in the system? For a customer named Jennifer Jones, what is the probability she spends > 10 mins in the system? For any customer you can name, what is the probability that he/she spends > 10 mins in the system? So, what proportion of customers spend > 10 mins in the system?For a customer named John Smith, what is the probability he spends > 10 min in the system? For a customer named Jennifer Jones, what is the probability she spends > 10 mins in the system? For any customer you can name, what is the probability that he/she spends > 10 mins in the system? So, what proportion of customers
  • #1
lina29
85
0

Homework Statement


For an M/M/1 queuing system with the average arrival rate of 0.4 min^−1 and the average service time of 2 minutes, compute
A- the expected response time in minutes;
B- the fraction of time when there are more than 5 jobs in the system;
C- the fraction of customers who don't have to wait until their service begins


Homework Equations





The Attempt at a Solution


For A I got that λ_A= 2.5 and that λ_S= 1/2 and then r would be 5. Obviously that's wrong since r has to be less than 1 I just don't understand where I messed up.
 
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  • #2
lina29 said:

Homework Statement


For an M/M/1 queuing system with the average arrival rate of 0.4 min^−1 and the average service time of 2 minutes, compute
A- the expected response time in minutes;
B- the fraction of time when there are more than 5 jobs in the system;
C- the fraction of customers who don't have to wait until their service begins


Homework Equations





The Attempt at a Solution


For A I got that λ_A= 2.5 and that λ_S= 1/2 and then r would be 5. Obviously that's wrong since r has to be less than 1 I just don't understand where I messed up.

λ_A = 0.4, not 2.5.

RGV
 
  • #3
Thank you!
so for A-10 and for C-.2 which were correct

I'm still stuck on part B though. I know I'm supposed to find out P(X<5) but I don't know how I'm supposed to find it
 
  • #4
Hi lina29! :smile:

Did you know that P(X<5)=P(X=0)+P(X=1)+P(X=2)+P(X=3)+P(X=4)?

Actually, if you know what the sum of an geometric series is, it turns out that it's even easier to calculate P(X≥5)=P(X=5)+P(X=6)+...
 
  • #5
Thank you!
 
  • #6
A slight extension to this question:

Given we know the arrival rate (λ)= 0.4 /min and the average service time (ε) = 0.5/min

How would one go about finding the proportion of customers who are in the shop more than 10min?

I am really unsure about how to approach this.
The probability of a customer being in the shop (ie queueing) for more than 10mins can be solved P(W>10)=exp(-(ε-λ)x10))

But what of the proportion of customers who spend more than 10 mins in the shop?

Thank you for any help!
 
  • #7
B.O.B. said:
A slight extension to this question:

Given we know the arrival rate (λ)= 0.4 /min and the average service time (ε) = 0.5/min

How would one go about finding the proportion of customers who are in the shop more than 10min?

I am really unsure about how to approach this.
The probability of a customer being in the shop (ie queueing) for more than 10mins can be solved P(W>10)=exp(-(ε-λ)x10))

But what of the proportion of customers who spend more than 10 mins in the shop?

Thank you for any help!

For a customer named John Smith, what is the probability he spends > 10 min in the system? For a customer named Jennifer Jones, what is the probability she spends > 10 mins in the system? For any customer you can name, what is the probability that he/she spends > 10 mins in the system? So, what proportion of customers spend > 10 mins in the system?
 

1. What is the M/M/1 queue system?

The M/M/1 queue system is a mathematical model used to analyze the performance of a single-server queueing system. It assumes that arrivals and service times follow a Poisson distribution, and that there is only one server available to service the queue.

2. What is the significance of calculating A, B, and C in the M/M/1 queue system?

Calculating A, B, and C allows us to determine important performance measures such as the average number of customers in the system, the average waiting time, and the average length of the queue. These measures help us understand and optimize the performance of the queue system.

3. How do you calculate A, B, and C in the M/M/1 queue system?

A is calculated using the formula A = λ / (μ - λ), where λ is the arrival rate and μ is the service rate. B is calculated using the formula B = λ / μ, and C is calculated using the formula C = λ / (μ * (μ - λ)).

4. What are the assumptions made in the M/M/1 queue system?

The M/M/1 queue system assumes that arrivals and service times are independent and follow a Poisson distribution. It also assumes that there is only one server available to service the queue and that customers are served on a first-come, first-served basis.

5. How can the M/M/1 queue system be applied in real-world situations?

The M/M/1 queue system is commonly used to model customer service systems, such as call centers, banks, and supermarkets. It can also be applied to other queueing situations, such as traffic flow and computer network congestion.

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