Solving Queuing Theory Problem: Airport Costume Area

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In summary, the problem is to minimize the mean time for 700 passengers to complete service at an airport costume area with 16 costume agents, where 65% are citizens and 35% are foreigners. The service times for citizens are exponentially distributed with a mean of 40 seconds, while the service times for foreigners are exponentially distributed with a mean of 75 seconds. The solution involves assigning a certain number of agents to serve citizens and the remaining agents to serve foreigners, in order to minimize average queueing times for both groups.
  • #1
saei
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Homework Statement



I have a queuing problem. In an airport, 700 passengers arrive at the costume area uniformly distributed over a 20 minutes period. 65% are citizen and 35% are foreigner. we have 16 costume agents each of them handles either citizens or foreigners (not both). the times of costume agents to process citizens are exponentially distributed with 40 seconds and the service time for foreigners are exponentially distributed with mean 75 seconds. There are two queues, one for citizens and the other for foreigners. when a costume agent becomes free, the first one in appropriate queue goes to the agent. how many agents should serve citizens and home many should serve foreigners in order to minimize the mean time (time that a passenger arrive at the costume area to the time that the passenger completes service with a costume agents).

Homework Equations



I try to Use M/M/m equations but the traffic intensity becomes greater than 1 and system will go to un-stability.

The Attempt at a Solution

 
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  • #2
I think after those 20 minutes, no more passengers arrive and the agents have enough time to clear the queue.

Given the large number of passengers and the small number of possible answers (1 to 15), I wonder if it could be sufficient to consider the average cases for some unknowns.
 
  • #3
mfb said:
I think after those 20 minutes, no more passengers arrive and the agents have enough time to clear the queue.
Yes, that's how I read it.

Also, the arrival rate to each queue so far exceeds the mean service times that it might be a reasonable approximation to suppose that the queues do not fall empty before the 20 minutes. This means we can just consider the emptying of two queues of known initial length.

I would start by evaluating the total average load on each queue (passengers x service time). As mfb says, this will give you a good first guess at the answer.

If there are n agents serving a queue, each with exponential service time parameter λ, what is the service time distribution for the queue?
 
  • #4
Thank you

Thank you for your help, but I am still confusing :D
 
  • #5
Given the average service time of a citizen and the number of them, what is the average total agent time to serve all of them? Similarly for the foreigners. How do those times compare?
 
  • #6
Unfortunately, there is not any other information :(
 
  • #7
saei said:
Unfortunately, there is not any other information :(

You have all that information.
 
  • #8
I calculated the mean total service time for all the citizens and foreigners.
for citizens : 18200 seconds
for foreigners : 18375 second
Now, according to the fact that total number of citizens are more than foreigners, I should assign more agents for citizens in order to reduce the waiting time of them in the queue to achieve the minimum response time.
Is it true?
But, I could not calculate the response time, because all the formula that I have are for steady state systems and it is not steady state. !
 
  • #9
saei said:
I calculated the mean total service time for all the citizens and foreigners.
for citizens : 18200 seconds
for foreigners : 18375 second
Now, according to the fact that total number of citizens are more than foreigners, I should assign more agents for citizens in order to reduce the waiting time of them in the queue to achieve the minimum response time.
Is it true?
That is true.

I don't know how to treat this properly without approximations.
 
  • #10
saei said:
I calculated the mean total service time for all the citizens and foreigners.
for citizens : 18200 seconds
for foreigners : 18375 second
Now, according to the fact that total number of citizens are more than foreigners, I should assign more agents for citizens in order to reduce the waiting time of them in the queue to achieve the minimum response time.
Is it true?
But, I could not calculate the response time, because all the formula that I have are for steady state systems and it is not steady state. !

I agree with the other posters that the problem is to clear out all 700 passengers, with no new passengers arriving.

The total service times of citizens and foreigners are fixed and uncontrollable by any policy, so we might as well neglect them and just try to minimize the average queueing time of customers; these are the times customers spend in their queues, before starting service.
If we assign nc servers to customers, then nc of the customers spend no time in their queue, while the remaining Nc = 455-nc do spend time in the queue. The queueing time of the first customer in the queue is ETc/nc, where ETc = average service time of a citizen; this is true because the rate that citizens leave service (when all servers are busy) is nc/ETc; in fact, the time until his service is the minimum of nc iid exponential random variables, which is again exponential with rate of nc times the rate per server. Similarly, the second customer in the queue spends an average time of 2*ETC/nc waiting for service, while the third customer waits an average of 3*ETc/nc, etc. So, what is the average of all the citizens' queueing times, in termns of nc?

Do the same computation for the foreigners, where nf servers are assigned to them. Now figure out how to combine the averages of the citizens and the foreigners into some type of overall average; this will be a not-too-complicated function of nc and nf. You want to minimze it, subject to having nc+nf = 16.
 
  • #11
saei said:
I calculated the mean total service time for all the citizens and foreigners.
for citizens : 18200 seconds
for foreigners : 18375 second
Now, according to the fact that total number of citizens are more than foreigners, I should assign more agents for citizens in order to reduce the waiting time of them in the queue to achieve the minimum response time.
Is it true?
But, I could not calculate the response time, because all the formula that I have are for steady state systems and it is not steady state. !
So let's try a fairly crude approach.
If there are n in a queue, and the expected time to service the whole queue is t, what is the expected total waiting time?
 

FAQ: Solving Queuing Theory Problem: Airport Costume Area

What is queuing theory and how does it apply to airport costume areas?

Queuing theory is a mathematical approach to analyzing waiting lines or queues. It helps us understand the behavior and performance of waiting lines in various systems, including airport costume areas. By using queuing theory, we can optimize the flow of people through the costume area, reduce waiting times, and improve overall efficiency.

What factors are considered when solving queuing theory problems in airport costume areas?

There are several factors that are taken into account when solving queuing theory problems in airport costume areas. These include the number of people waiting in line, the arrival rate of people, the service rate of the costume area, the layout and design of the area, and any potential bottlenecks that may affect the flow of people.

How do you determine the most efficient queuing system for an airport costume area?

To determine the most efficient queuing system for an airport costume area, we use queuing models such as the M/M/1 model or the M/M/c model. These models take into account the arrival rate, service rate, and number of servers to determine the optimal queuing system for the given parameters.

Can queuing theory help reduce waiting times in airport costume areas?

Yes, queuing theory can help reduce waiting times in airport costume areas. By using queuing models and analyzing the various factors involved, we can identify potential areas for improvement and make changes to the system to reduce waiting times. This can lead to a more efficient and pleasant experience for travelers.

What are some real-world examples of queuing theory being applied to airport costume areas?

One example is the implementation of multiple service counters in airport costume areas to reduce waiting times. Queuing theory was used to determine the optimal number of counters needed based on the arrival and service rates. Another example is the use of virtual queuing systems, where travelers can reserve a spot in line through their mobile devices, reducing the need to physically wait in line. This also utilizes queuing theory principles to improve the overall experience for travelers.

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