i saw a previous question about something like my issue but i couldn't make it work as suggested in the answer.
I have 5 sources that generate 5 different agents to be stored via a rackStore block in a rackSystem; a resource from a resource pool pick them up (rackPick block) and give them to an assembler. At some point i seize the same resource to do other tasks but the simulation is interrupted when the rack is full. I tried to make the sources stop when the rack is full in this way:
if( rackSystem.isFree(1, 1, 1) == false)
self.set_rate(0);
I typed this code in each source "on exit" bar but it doesn't work; what am i missing?
The rackSystem is made of 5 different palletRack blocks, each with 1 row/position/level.
Thanks for your advices.
You are only checking if the position (0,0,0) is free. Instead, amend your condition to this:
if( rackSystem.hasSpace() == false) self.set_rate(0);
Related
I have a pretty simple Anylogic DE model where POs are launched regularly, and a certain amount of material gets to the incoming Queue in one shot (See Sample Picture below). Then the Manufacturing process starts using that material at a regular rate, but I want to check if the material in the queue gets outdated, so I'm using the TimeOut option of that queue, in order to scrap the outdated material (older than 40wks).
The problem is that every time that some material gets scrapped through this Timeout exit, the downstream Manufacturing process "stops" pulling more material, instead of continuing, and it does not get restarted until a new batch of material gets received into the Queue.
What am I doing wrong here? Thanks a lot in advance!!
Kindest regards
Your situation is interesting because there doesn't seem to be anything wrong with what you're doing. So even though what you are doing seems to be correct, I will provide you with a workaround. Instead of the Queue block, use a Wait block. You can assign a timeout and link the timeout port just like you did for the queue (seem image at the end of the answer).
In the On Enter field of the wait block (which I will assume is named Fridge), write the following code:
if( MFG.size() < MFG.capacity ) {
self.free(agent);
}
In the On Enter of MFG block write the following:
if( self.size() < self.capacity && Fridge.size() > 0 ) {
Fridge.free(Fridge.get(0));
}
And finally, in the On Exit of your MFG block write the following:
if( Fridge.size() > 0 ) {
Fridge.free(Fridge.get(0));
}
What we are doing in the above, is we are manually pushing the agents. Each time an agent is processed, the model checks if there is capacity to send more, if yes, a new agent is sent.
I know this is an unpleasant workaround, but it provides you with a solution until AnyLogic support can figure it out.
I have 2 storages (called storageA & storageB) and I want to move an agent (pallet) from one to the other via forklifts. I have set up the following.
A pallet is created at a node and is moved to storageA via 'store'. This part works fine. The pallet is then moved to storageB via 'store1' after a delay. This is when the following error occurs:
Exception during discrete event execution:
root.store1.seizeTrans.freeSpaceSendTo:
Path not found! {agent=2, source={level=level, pos=(1673.3333333333333, 3245.0, 0.0)}, target={level=level, pos=(1857.25, 3160.4845, 0.0)}}
It works if I replace 'store1' with a retrieve block and send it to a node first. However I would like to send the pallet directly to another storage rather than via another location. Is this possible?
Please let me know if I have not provided enough information.
Thanks
yeah unfortunately you can't do that as far as I know, the solution I use is the following, which is actually not a super robust solution... but has been ok in applications so far
Place a retrieve block between your delay and your store1
Use the agent you pick up as destination:
on the on seize action of the retrieve block do:agent.transporter=unit;
4.On the store1 block put the highest priority for the task
5. ON the store1 block use resource custom transporter choice: agent.transporter.equals(unit)
6. The dispatching policy should be nearest to the agent in store1, but doing all the above ensures that the resource continues doing the task no matter what... by only using the dispatch policy your model will work 99.999999% of the time... the problem occurs only if another task with higher priority occurs at the exact same time as the transporter is released in the retrieve block, which is rare, but can happen.
I had the same question today so I landed here. But luckily, only after the second step written above, the whole process needed did already work for my case. We can move an agent from one storage to another by simply set the destination of the 'retrieve' block to the coordinate of the agent and the move to independently instead of by fleets or resources. after that we put the 'store' block.
Destination is: (x,y,z)
X: agent.getX()
Y: agent.getY()
Z: agent.getZ()
after agents being retrieved to a specified coordinate, it seems that fleets do not comply paths in the network anymore
I want to make agents to not enter the queue if it's full (if it's full then go to sink) at the moment of arrival in selectOutput5.
I tried to put "if-else" into "Actions" section
But I don't really know which parameter to use (tried to use queue.size and queue.capacity but I don't know how to code this properly), please help. Not sure if I doing the right thing at all by trying to put if-else into actions of selectOutput5
The model look like this:
You need to code the conditions under which they should enter which queue and then if the conditions are not met it will assess the next out option.
See example below
It will only go to queue 1 if the queue size is less than 5, else it will assess the queue size of queue 2 and if both are full then go to the exit.
The Actions section is only for code you want to execute if they do exit one of the out options.
Put a selectOutputOut block, select conditions there. And type below your condition: yourQueue.size()>=yourQueue.capacity(). Send the ones to Sink block when this condition is true.
I have the model which I posted before on Stack. I am currently running the iterations through 5 Flow Chart blocks contain enter block and service block. when agent fill service block 5 in flow chart 5, the exit block should start to fill block one and so on. I have used While infinite loop to loop between the five flow chart blocks but it isn't working.
while(true)
{
for (Curing_Drying currProcess : collection) {
if (currProcess.allowedDay == (int)time(DAY)) {
currProcess.enter.take(agent);
}
}
if (queue10.size() <= Throughtput1){
break;
}
}
Image for further illustration 1
Image for further illustration 2
Wondering if someone can tell me what is wrong in the code.
Based on the description and the pictures provided, it isn't clear why the while loop is necessary. The On exit action is executed for each Agent arrival to the Exit block. It seems that the intention is to find the appropriate Curing_Drying block based on number of days since the model start time? If so, then just iterating through the collection is enough.
Also, it is generally a good practice to provide more meaningful names to collections. Using simply collection doesn't say anything about the contents and can get pretty confusing later on.
I've been given a task to set up an openai toy gym which can only be solved by an agent with memory. I've been given an example with two doors, and at time t = 0 I'm shown either 1 or -1. At t = 1 I can move to correct door and open it.
Does anyone know how I would go about starting out? I want to show that a2c or ppo can solve this using an lstm policy. How do I go about setting up environment, etc?
To create a new environment in gym format, it should have the 5 functions mentioned in the gym.core file.
https://github.com/openai/gym/blob/e689f93a425d97489e590bba0a7d4518de0dcc03/gym/core.py#L11-L35
To lay this down in steps-
Define observation space and action space for your environment, preferably using gym.spaces module.
Write down the step function which performs agent's action and returns a 4 tuple containing - next set of observations from the environment , reward ,
done - a boolean indicating whether the episode is over , and some extra info if you want.
Write a reset function for the environment to reinitialise the episode to a random start state and return a 4 tuple similar to step.
These functions are enough to be able to run an RL agent on your environment.
You can skip the render, seed and close functions if you want.
For the task you have defined,you can model the observation and action space using Discrete(2). 0 for first door and 1 for second door.
Reset would return in it's observation which door has the reward.
Then agent would choose either of the door - 0 or 1.
Then perform a environment step by calling step(action), which will return agent's reward and done flag as true - signifying that the episode is over.
Frankly, the problem you describe seems too simple to accomplish for any reinforcement learning algorithm, but I assume you have provided that as an example.
Remembering for longer horizons is usually harder.
You can read their documentation and toy environments to understand how to create one.