How can i calculate idle time for all the agents entering through source and exiting into the sink.
I want to get these data as a table( agentID vs idle time) as well as in a plot which gives average idle time.
I don't know much java either and this is my first assignment in anylogic. Learning through you tube videos.
Related
I am developing a logistics simulation in the factory by Anylogic. It's a pick up and delivery problem, where the AGVs need to pick up the parcel and deliver to the target location. All the AGVs are traveling following paths. The paths have different speed limits.
My goal is to reduce the time of traffic jam or waiting time for jobs to be picked up.
I have the leading time, job delivered time - job generated time.
But I from here, I want to identify the time of traffic jam or waiting time.
Is there a way to calculate the time from one spot to the other considering different speed limit of paths without waiting time or traffic jam? So that I could subtract this from leading time.
Let me know if I need to clarify something.
There is no build-in way to do this, you have to do it yourself. I have 3 ideas:
You compute this mathematically in the model yourself, i.e. write a function that computes the length of the total path and you have the ideal speed already, voila
You run a separate experiment and turn off all speed limits and other traffic: record the time in that ideal case and use that to compare
Similarly, you could do this in the same experiment during a warmup period: drive a fake transporter along the path and compute the perfect durations
I'm quite a beginner in Anylogic, so maybe my question is moronic.
What I'm trying to do is to create a model of M/M/1 with reneging, i.e. an agent waits in queue for a (random) amount of time and then exits the queue via timeOut.
Also, I've inserted timeMeasureStart and timeMeasureEnd in order to find the mean time spent in queue for the agents which left the queue by timeOut: MM1 with reneging.
I've tried to set constant time, uniform, triangular and normal random time - the mean time (and the deviation) was as the theory predicts.
But when I tried to use exponential (and weibull), the mean time was significantly less then the mean value of the distribution.
I wonder if someone could explain to me why it happens?
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 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.
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.
enter image description here
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);