I have a simple source to sink model and I am merely altering the "Rate" to 6 per hour. I would expect a fixed 6 agents to be generated each hour, but it seems like in the first hour from 0 to 60min, only 3 agents are generated. Similarly in the time 60-120min, only 5 agents were generated.
Is there a warm up period in Anylogic or something like this that explains what is happening?
Another alternative is to just use the interarrival time with a fixed time. This will give you the same results as Felipe's answer, but with one less object, as you will not need the event.
A few important items to note on this approach:
Instead of 6.0, using a parameter would be better. You could call this parameter dArrivalsPerHour. This would make your source block easier to read in the future, and give you some better flexibility. Your interarrival time would be 1.0 / dArrivalsPerHour.
Make sure you divide by at least (1) double. If you did 1/6, java would actually return 0! This is because in Java two integers divided by each other returns an integer, so java just truncates the decimal. If you use a parameter, just set its type to double. Usually to be extra careful against anyone accidentally changing my parameter type to integer in the future, I would still go ahead and use a 1.0.
AnyLogic does not have an arrival at time zero in this approach. The first arrival would be at 0.166 hours. If you want an arrival at time zero, followed by this pattern (it would still be 6 per hour, just shifting when it starts), then you have a couple of options. First, you can use Felipe's approach and set the first occurrence time to zero. An alternative would be to could call an inject On Startup OR after you have finished any initialization code your model has.
Happy Modeling!
The source block doesn't produce exactly 6 agents per hour, it produces agents using a poisson distribution with mean 6 per hour (lambda=6). So the number of agents per hour you get will be random. But the reason why you always get 3 in the first hour and 5 in the second hour is that you have a fixed seed:
You can find that option clicking on your simulation experiment under the randomness tab. If you change to random seed it will produce different agents per hour instead of always 3 and 5.
To produce EXACTLY 6 per hours you need to use an event. But first create a source that generates agents through injection:
And the event running 6 times per hour, adding 1 agent to the source:
Related
Every time I run a simulation with the same parameters in the Run window I get exactly the same results. The results are different if a different number of replications is set each time the run is started
These are my settings in the run window:
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I have a lot of Process blocks. Most of them have a normal distribution in duration. Why are the results not different?
If it helps in any way, her is a photo of the constructed model:
enter image description here
Arena uses the same random nr stream for your run unless you tell it to use another - so your first rep will look the same every time. The answer depends on the distributions you sample from. If you change the logic and sample at other times, the answer will change. Each following rep will have a unique answer based on the random nr streams you are sampling from. It makes it easier/possible to find errors if you can execute exactly the same run.
Arena provides (by default) ten different "streams" of (pseudo) random numbers. If you don't ask the system to use a particular stream, it will use stream 10. For example NORM(10,2) will use stream 10 to calculate a random normally distributed number (mean 10, standard deviation 2); NORM(10,2,4) will use stream 4 to calculate a similarly distributed number.
By default, the 10 random number generators for the streams are initialised at the beginning of each run to 14561, 25971, 31131, 22553, 12121, 32323, 19991, 18765, 14327, and 32535 (from Arena help). At the end of one replication, the generators will not be re-initialised, so they will start the next replication with a new value.
You can control the random number generator initialisation with the SEEDS element.
As #Marlize says, this helps to ensure that you can reproduce a simulation result if you need to.
Currently, I have two delay blocks above each other, where one agent goes through one of the blocks and the other through the other one.
But when I want exponentially distributed values with a mean of 120 seconds, They both need to have the same value always. So they are done at the same time.
You simply need to have the two delay blocks use their own (but with the same seed) random object.
Start off by creating two identical random objects
And have each of the delay blocks use of them of them
Then the numbers they will sample will be the same for every sampling iteration.
See this post for a similar problem
Why do two flowcharts set up exactly the same end with different results every time the simulation is run even when I use a fixed seed?
Not questioning your probably bad design by not using resources, These are the steps to follow to ensure things happen at the exact same time:
1.Create a variable called seed of type long
2.create a cyclic event that runs every 1 minute and has the following code:
seed=(new Random()).nextLong();
3.In both blocks you will use the following code to calculate the exponential distribution:
exponential(120,0,new Random(seed))
Anybody has a reference for how AnyLogic implements it's rate per day? Specifically, my agent is at different locations (based on time of day) throughout the day. If there are 10 triggers a day, do they happen randomly for each agent throughout the day, or only at the beginning of a day (when agent is at home), etc.?
Thank you, Amy! Your explanation was very helpful.
The rate follows the Poisson distribution. If you divide 1/rate, you will get an inter-arrival time that follows the exponential.
As this is random, you may not actually get 10 a day - you may get 9 one day and 11 the next. If you want to get exactly 10 in a day, you need to think about writing your own code to make that happen. That might be something like generating 10 dynamic events randomly sampled times that all trigger a transition in their action code (that would not be exponential between events).
I'm trying to test example of VRPTW with depot usage constraint -
from here.
If I change VehicleNumber on different value(for example from 4 to 6), solution will never be found. This example only works with the specified property values. Why?
I checked C# and Python examples, result is the same.
Because the problem is over constrained with 6 vehicles.
This code creates one interval per vehicle. These intervals have a fixed duration and a maximum end time. 4 such intervals fit in the allowed time, 6 do not.
I have a complex ADF's pipeline with slice based scheduling, where slice = day.
Now it works like that:
Day1, Day2, Day3, ..., PreviousDay, CurrentDay
At 00:00 AM of CurrentDay it reprocess PreviousDay. So for Today i have calculated data for the previous day only.
I need to change the schedule to make it works like that:
1) slice size should be left the same = day
2) reprocessing for CurrentDay should be triggered 4 times per day to emulate results refresh (kinda running total)
The reason why i wanna leave the same slice size = 1 day, because it is a partition sizeof underlying tables. I dont wanna make them small as a few hours because it is meaningless for the current volume of data.
Cannot realize how to avoid change size of slice to a few hours and achive this goal. How to force reprocess current day? Any ideas will be helpfull for me.
Thank you.
The way to do this is to make 2 changes:
Set the availability to be StartOfInterval, thus running the CurrentDay instead of PreviousDay. Dataset availability and policies
Set the schedule of the activity to Hourly with frequency 8 (thereby running this 4 times per day) (See data-factory-scheduling-and-execution#specify-schedule-for-an-activity for more info) The activity and output should have matching slices, this can be fixed with the description below.
Since the slices of the input (Day:1) and activity (Hour:8) is different, you need to set two extra parameters in the activity for the input, to change the slice from 8 hours to 1 day, thus matching the input. The execution is based on the output slice. This is explained further here: https://learn.microsoft.com/en-us/azure/data-factory/data-factory-scheduling-and-execution#model-datasets-with-different-frequencies The Activity and output slice also have different slices and can be fixed with the same method.