I want to stop the model at a specific model time.
Do I have to work with a counter variable per time and then throw stopSimulation() or is there another possibility? My simulation will run for one week in model time. I want to stop the simulation 5min before it will end, so 5min before one week of model time is over.
You can specify the stop time in the simulation experiment properties. See below:
In the settings of Simulation:main you can define exactly when you want your simulation to stop.
See attached image:
To set a week less 5 minutes, replace the number 100 with the number 10,075 (assuming your model runs in units of minutes)
Good luck
Related
i am new to carla and have one question regarding the statement (below mentioned) in carla docu:
how to understand the simulation time and time step mentioned in the statement? Is this same as rendering frame?
"There is a difference between real time, and simulation time. The simulated world has its own clock and time, conducted by the server. Computing two simulation steps takes some real time. However, there is also the time span that went by between those two simulation moments, the time-step."
Thank you for your help!
So you might set a simulation time of 5 seconds to model something - like how far the ripples progress in water when a stone hits the surface.
But the computer/processor may take 5 minutes to complete all the calculations to provide that solution.
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.
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 would like to get the mean waiting time of each unit spending in my queue of every hour. (so betweeen 7-8 am for example 4 minutes, 8-9 10 minutes and so on). Thats my current queue with my timemeasure Is there a way to do so?
]
Create a normal dataset and call it datasetHourly. Deactivate the option Use time as horizontal value. This is where we will store your hourly data.
Creat a cyclic event and set the trigger to cyclic, once every hour.
This cyclic event will get the current mean of your time measurement ( waiting time + service time in your example) and save this single value in the extra dataset.
Also we have to clear the dataset that is integrated into the timeMeasurementEnd, in order to get clean statistics again for the next hour interval.
datasetHourly.add(time(HOUR),timeMeasureEnd.dataset.getYMean());
timeMeasureEnd.dataset.reset();
You can now visualise the hourly development by adding the hourlyDataset to a normal plot.
Is it possible to have Silk Performer recalculate results based on a specific time period from testing? What I am seeing is a spike at the end of my test. This needs investigated, but I would like to show that prior to that spike, the average time was good. Because of this spike I am getting a couple seconds higher - at least that is my assumption right now. I would like to show that before the spike the times are good.
Here is what I am seeing:
In the Silk Performance Explorer there is a resample option under results. You can set the specific time period for calculation there.