I've a question. In my model I want to model patients/employees in a hospital environment as agents. Due to the big amount of patients/employees in the hospital (>4000), my model runs very slow (which is logical, I know). Because I want the patients employees to block eachother and AGVs, I let them move by a transporterfleet (which has >5000 capacity), by doing this method I can make it possible to let them block eachother.
Now what I want is that when the patient or employees arrive to the location departments they disappear for hours/minutes as long as there appointment or workschedule is saying to them. The most perfect is to just delete them for example 4 hours of runtime, so that I will only have the moving agents in my model, is there a way to do this? So that when a patient/employee arrives at an appointment, the agent and transport disappears for 4 hours and returns after this delay, keeping in mind that it should speed up the run-speed of my simulation (otherwise I just can use a delay block, but than my model keeps very slow). The transporters are making the model really slow.
Or perhaps another method will be better to model the patients and employees with the feature that they are blocking AGVs? An option which I should think of is that an moving agent is constantly checking if there is an agent close to him every second, but I do not know if this will be speed up the runtime or just will slow it down even more with >4000agents.
Or another option is that I only let the AGVs check if there are agents around them every second just by coding(this will only be around 40 agents).
Also you see that it is only using 5% of my memory data..
Thanks.
Related
I am trying to simulate a manufacturing assembly process, where material items are processed following an unique line. In the quality control stations, when a failure is detected, the object is sent to the repair area (by a truckpallet) and, when it is repaired, the same resource takes it and puts it at the start of the line. Until this point, I already programmed it.
The problem is the following: when it is a repaired object, is has to follow the same conveyor but with no stops in the stations. The object must enter a station and leave it, with no delays (as the works related with the stations have already been made).
I thought the best would be to consider the difference (repaired vs. not repaired) in the Agent, but then I can't work with it in the Main agent... I have also tried alternative solutions, for example defining variables in each station 1 and consider that in the stations delays and in the following station:
triangular( 109.1*delay_bec, delaytime_bec*delay_bec, 307.6*delay_bec)
Actions - in finished process:
if(delay_bec==0){
delay_headers=0;
delay_bec=1;}
But nothing worked... Any help?
I thought the best would be to consider the difference (repaired vs. not repaired) in the Agent, but then I can't work with it in the Main agent...
This is actually the correct approach. You need to create a custom agent type, give in a boolean variable isRepaired (or similar) and then in the delay you can dynamically adjust the duration using that characteristic:
agent.isRepaired ? 0. : 100
This will delay normal agents by 100 time units and repaired agents not at all.
Obviously, you must make sure that the agents flowing through the flow blocks are of your custom agent type (see the help how to do that)
I have in my model some free-moving agents, which travel to specific nodes. I use the function...
moveTo(node)
...to specify the node an agent should visit. Using this function, the agent travels the shortest path to the node. However, the model layout contains areas (i.e. image files), which the agent should not pass. Right now, the agents may travel through these areas to reach their destination. Now I'm wondering, whether there is an easy way to permit an agent to enter specific areas in the model, when traveling to a node.
I already took a look at the example model "Wandering Elephants" where the elephants are permitted to walk through areas with water. The solution there is, that if an elephant meets water in the direction it's currently heading, it randomly searches for another direction, until it finds one without water. However, this approach doesn't really fit to my problem, as the elephants in the model wander around without any specific destination. I'm searching for a method, which works for an agent that travels to a specific point. In the best case, the agent would search the shortest path around the obstacle to reach its destination.
Edit 1: The following figure shows my problem in a nutshell. On the left side is my model structure, while on the right side the state chart of my custom agent. What is happening in the model: The 3 sources are producing agents, which will be delayed for an uncertain time (delay stops with stopDelay()). Everytime an agent enters a delay, the delay is added to the collection request. My customagent check requests in a loop until the collection contains at least one request. Then, the customagent randomly selects a request (i.e. delay object) to serve. Each delay is associated with a node (the collection processNodes maps delays to nodes). Now, I want to cast my customagent to a Transporter and move it to the corresponding node. The agent should avoid collisions with the stripped walls in the model. I want to avoid any seizing and releasing of resources. I just want to adapt the behaviour of the Transport agent from the material handling library to my agent.
Edit 2:
In my current testbed, my custom agent does not consider node 1 or node 2. For testing, the agent should only try to reach node without any collisions.
I found a sufficient work-around. Not exactly what I wanted, but it works. Against my initial intention, I use now seize and release for transports. However, I added a hold-block in front of each seized-block and only a resource, which decides to serve the process, is able to unblock the corresponding hold. The on-enter control of the unblocked hold ensures that the hold is directly blocked again as soon as a single agent flows through. For the case that other users are also interested in the solution, I attached the flow-chart of the process and the state-chart of the Transporter-Agent. The system structure is quite the same as in my initial question.
There is no build-in way unless you use transporters from the Material handling library (or pedestrians). These can do what you need.
So easiest might be to convert you agents to transporters temporarily.
Otherwise, you will have to code something yourself...
I am interested in capturing the time a particular material handler(AGV in my case) spends at a particular node before it is released. Is there a way to do so?
This works in general, since I don't know anything about your model (there are many other ways depending on what you are doing):
Create a variable and make it equal to time when your AGV arrives to the node:
timeWhenArrivesToNode=time();
Create another variable and make it equal to the amount of time it spent in that node... This code should be executed at the moment when the AGV leaves the node:
timesWhenItIsReleased=time()-timeWhenArrivesToNode;
Of course the answer will have the time units of your model.
I am making simple distribution center in Anylogic.I did make truck agent and i am able to move it from one gis point to another gis point.
But I want to load some other agents(Let's say banana agent) into my truck agent and then trucks start their journey(if truck is full of banana).How can i do this?
I hope you have already solved your problem from almost a year ago. However, since there is no specific answer, I'll leave it here for anyone who might get stuck with the same problem.
Anylogic's Process Modelling Library (PML) has an element called Pickup and its opposite, Dropoff. This is used to do exactly what you asked: to load some element into a transporter (either a truck, a forklift, or even a person).
To use the block as you asked you would need a topology like in the picture:
The Queue elements are necessary to hold elements until the pickup occurs.
The Pickup element might pick elements in three modes:
While a given condition is True;
An exact amount (if available);
All available agents.
I'm assuming all trucks must be completely filled up to its maximum capacity. Hence, the chosen mode will be the second one where the exact amount will be TruckCapacity, a parameter of agent Truck.
The selected mode picks up agents (in this case Bananas) up to the desired amount. However, if nothing is available or the present amount is inferior to the desired, the native behavior of the Pickup block is to allow the container element to simply go through it and pick only what's available.
To prevent such behavior, I've created a restricted area where only 1 Truck can be at a time. Additionally, the Hold block WaitFullyLoaded (set to initially blocked) forces the container agent Truck to be fully loaded. Whenever a Banana enters the Queue waitTruck, a verification is performed to check if 1 Truck can be filled. If so, allows passage for that one truck:
if(self.size()/TruckCapacity>=1){
WaitFullyLoaded.unblock();
}
To block WaitFullyLoaded again, when the truck passes through the restrictedAreaEnd block, it performs WaitFullyLoaded.block();
The main idea is this. However, many features can be added and changed.
Hope this helps,
Luís
Let's say we have a reactive sales forecasting system.
Every time we make a sale we re-calculate our Forecast for future sales.
This works beautifully if there are lots of sales triggering our re-forecasting.
What happens however if sales go from 100 events per second, to 0. And stay 0 for a long time?
The forecast we published back when sales were good stays being the most up to date forecast.
How would you model in this situation an event that represents 'No sales happening' without falling back to some batch hourly/minutely/arbitrary time segment event that says 'X time has passed'.
This is a specific case of a generic question - How do you model time passing with nothing happening in an event based system - without using a ticking clock style event which would wake everyone up to reconsider their current values [an implementation which would not scale].
The only option I have considered that makes sense:
Every time we take a sale, we also schedule a deferred event 2 hours in the future that asks us to reconsider our assessment of that sale.
In handling that deferred event we may then choose to schedule further deferred events for re-considering.
Considering this is a very generic scenario, you've made a rather large assumption that it's not possible to come up with a design for re-evaluating past sales in a scalable way unless it's done one sale at a time.
There are many different scale related numbers in the scenario, and you're only looking at the one whereby a single scheduled forecast updater may attempt to process a very large number of past sales at the same time.
Other scalability issues I can think of:
Reevaluating the forecast for every single new sale doesn't sound great if you're expecting 100s of sales per second. If you're talking about a financial forecasting model for accounting, it's unlikely it needs to be updated every single time the organisation makes a sale, if the organisation is making hundreds of sales a second.
If you're talking about a short term predictive engine to be used for financial markets (ie predicting how much cash you'll need in the next 10 seconds, or energy, or other resources), then it sounds like you have constant volatility and you're not really likely to have a situation where nothing happens for hours. And if you do need forecasts updated very frequently, waiting a couple of hours before triggering a re-update is not likely to get you the kind of information you need in the way you need it.
With your approach, you will end up with one future scheduled event per product (which could be large), and every time you make a sale, you'll be dropping the old scheduled event and scheduling a new one. So for frequently selling products, you'll be doing repetitive work to constantly kick the can down the road a bit further, when you're not likely to ever get there.
What constitutes a good design is going to be based on the real scenario. The generic case is interesting to think about, but good designs need to be shaped to their circumstances.
Here are a few ideas I have that might be appropriate:
If you want an updated forecast per product when that product has a sale, but some products can sell very frequently, then a good approach may be to throttle or buffer the sales on a per product basis. If a product is selling 50 times a second, you can probably afford to wait 1 second, 10 seconds, 2 hours, whatever and evaluate all those sales at once, rather than re-forecasting 50 times a second. Especially if your forecasting process is heavy, doing it for every sale is likely to cause high load for low value, as the information will be outdated almost straight away by the next sale.
You could also have a generic timer that updates forecasts for all products that haven't sold in the last window, but handle the products in buffers. For example, every hour you could pick the 10 products with the oldest forecasts and update them. This prevents the single timer from taking on re-forecasting the entire product set in one hit.
You could use only the single timer approach above and forget the forecast updates on every sale if you want something dead simple.
If you're worried about load from batch forecasting, this kind of work should be done on different hardware from the ones handling sales.