Hi I am a beginner at AnyLogic. I would appreciate if someone could help me. I have the task to create a call center model in which I have 3 customer service representatives, Customers calls arrive to the call center according to a Poisson process with rate λ = 15 per, The customer service times are exponentially distributed with a mean of 10 minutes. There are 24 phone lines and in case all lines are busy then the call is lost. What is the easiest way to limit queue space in the waiting area?
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I need to model a waiting line in a call centre in AnyLogic. This is what I don't understand. It says:
If all of the service representatives are busy, an arriving customer is placed on hold, but ties up on the phone lines.
I am not sure what block or how to model customers waiting. Can someone help me? Thank You!
Here is my solution, although I'm absolutely sure other methods exist.
To represent an arrival rate of 15/hr, use a source block with arrivals defined by rate, with the rate set to 15 per hour.
To represent 24 phone lines and 3 service reps, use a queue block (callsWaiting) followed by a delay block (service). The queue block should have capacity = 21 and the delay block should have capacity = 3 with a delay time of exponential(0.1,0) minutes representing the exponential service time (with mean 10 min).
To represent losing calls when all of the phone lines are tied up, place a selectOutput block before the callsWaiting queue and set its condition to: callsWaiting.canEnter(). It will return false if the queue is at maximum capacity. On the false branch for that selectOutput, place a sink block for dropped calls.
I have to calculate the probability of a customer waiting more than 5 min in the queue in anylogic. I've already implemented the timemeasureend and-start block, but I have seriously no clue how to compute the probability of a customer waiting longer than 5min? What do I need to write where? Help is highly appreciated
Thanks!
There are two objects in a process modelling library: TimeMeasureStart and TimeMeasureEnd. You can put those around a queue and record the time for each entity after they exit the queue. Save that time to a Statistics object and from there your probability if waiting more that 5 mins should be (no of samples over 5 mins)/(total number of entities). Also, make sure that your model time unit is set to minute to make it easier.
I am currently working on a simple simulation that consists of 4 manufacturing workstations with different processing times and I would like to measure the WIP inside the system. The model is PennyFab2 in case anybody knows it.
So far, I have measured throughput and cycle time and I am calculating WIP using Little's law, however the results don't match he expectations. The cycle time is measured by using the time measure start and time measure end agents and the throughput by simply counting how many pieces flow through the end of the simulation.
Any ideas on how to directly measure WIP without using Little's law?
Thank you!
For little's law you count the arrivals, not the exits... but maybe it doesn't make a difference...
Otherwise.. There are so many ways
you can count the number of agents inside your system using a RestrictedAreaStart block and use the entitiesInside() function
You can just have a variable that adds +1 if something enters and -1 if something exits
No matter what, you need to add the information into a dataset or a statistics object and you get the mean of agents in your system
Little's Law defines the relationship between:
Work in Process =(WIP)
Throughput (or Flow rate)
Lead Time (or Flow Time)
This means that if you have 2 of the three you can calculate the third.
Since you have a simulation model you can record all three items explicitly and this would be my advice.
Little's Law should then be used to validate if you are recording the 3 values correctly.
You can record them as follows.
WIP = Record the average number of items in your system
Simplest way would be to count the number of items that entered the system and subtract the number of items that left the system. You simply do this calculation every time unit that makes sense for the resolution of your model (hourly, daily, weekly etc) and save the values to a DataSet or Statistics Object
Lead Time = The time a unit takes from entering the system to leaving the system
If you are using the Process Modelling Library (PML) simply use the timeMeasureStart and timeMeasureEnd Blocks, see the example model in the help file.
Throughput = the number of units out of the system per time unit
If you run the model and your average WIP is 10 units and on average a unit takes 5 days to exit the system, your throughput will be 10 units/5 days = 2 units/day
You can validate this by taking the total units that exited your system at the end of the simulation and dividing it by the number of time units your model ran
if you run a model with the above characteristics for 10 days you would expect 20 units to have exited the system.
I'm trying to simulate a pedestrian flow in the entrance of an hospital.
We are installing check-in platforms and I want to know how many platforms we should get according to the patient flow.
I'm using Anylogic personal learning edition and when I put an arrival rate of 5 per hour during the simulation only 3 appears.
I'm trying to understand how anylogic works and distribute the pedestrians according to the rate we put.
For the personnal learning edition 1h equal 1min in real.
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if you choose rate=5, the pedSource block will generate pedestrians with an exponentially distributed interarrival time with mean = 1/rate = 1/5.
Which means that the average of arrivals on the long term will be 5, but you won't get 5 every hour since it's a stochastic variable.
If you change the seed, you will have different arrivals... click on Simulation: Main and you can change the seed or use a random seed:
Now if you really want exactly 5 per hour in a deterministic way, you need to change the arrival from rate to inject function:
Then you can create an event that runs cyclically 5 times per hour.. or 1 time every 12 minutes:
and you do pedSource.inject(1);
I want to be able to rank users based on how quick they have completed each level. I want this to be an overall leaderboard I.e. shortest overall time for all levels.
The problem here is that for each level completed the totally completion time goes up. But I want to ensure that the leaderboard takes that into account so that a user having completed 10 levels will rank more highly than someone with only 1 completed level.
How can I create some kind of score based on this?
Before submitting the time to leader board.
You could perform a modulation on the total time by the number of levels completed, then for each level completed reduce it by a set amount so people who complete all levels with the same average time will score better then people with the same average time but with fewer levels.
My Preferred Method:
Or you could express it with a score value.
level complete = 1,000.
Each level has a set time limit bonus, the longer you take the less bonus u get.
eg
I Complete the level in 102 secs Goal time is 120 secs
I get 1,000 points for completion and 1,500 points for each second
that i beat the Goal time for.
This way i will get 1,000 + (18* 1,500) = 28,000 points
Next guy completes in 100 secs
He Gets 1,000 + (20*1,500) = 31,000 points
I suggest adding a default amount of time to the total for each incomplete level. So, say, if a player beats a new level in 3 minutes, that replaces a 10 minute placeholder time, and they 'save' 7 minutes from the total.
Without that kind of trick, the iPhone has no provision for multi-factor rankings.
Leaderboard scores in GameKit have to be expressed as a single number (see this section of the GameKit Programming Guide), so that won't be possible.
Your best bet would be to just have a completion time leaderboard for people who have completed all the levels, and maybe another leaderboard (or a few) for people who have completed a smaller number of levels.