How to predict the inter-arrival distribution of a source?

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mike S4 asked Nov 02 2019 at 9:06 AM Brenton King commented Dec 13 2019 at 10:29 PM

How to predict the inter-arrival distribution of a source?

Hello everyone,

I need to vary the value associated with a label of each item in the warehouse based on the demand for arrival.

In my model I have a source with a known inter-arrival distribution, while the warehouse has items with a label that should be increased according to the arrivals: the more frequent these are, the more it increases and the less they are frequent and the less it increases.

Knowing the inter-arrival distribution of the source, is there a way, from the point of view of the warehouse, to estimate or predict the arrival distribution of the source and thus modify the label?

Thanks for the help.

Software Version:

FlexSim 19.0.0

source distributions inter-arrival time

· 6

Joerg Vogel commented · Nov 03 2019 at 12:38 AM

How long do you want a forecast into the future?
You can create from the statistical distribution several values for events in the future and store them in an array. When a creation event occurs, you return in interarrival time the first element of the array, destroy the element and append at the end a new value. You can get the next events from the array to estimate a forecast.

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mike S4 Joerg Vogel commented · Nov 03 2019 at 9:48 AM

@Jörg Vogel thanks for the answer. In my model I have to predict the daily arrival of customers in a shopping center, knowing the distribution of arrival. So, for example, if more customers arrive around 9:00 a.m., the labels' values of the items in the warehouse should increase rapidly during that period and accordingly if fewer customers arrive, the labels' values should grow more slowly. I need to know in advance how many customers are coming in that time. How can I implement this behavior into FlexSim?

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Braydn T mike S4 commented · Nov 05 2019 at 8:16 PM

@mike S4

We are having trouble determining exactly what you are supposed to do. If you are trying to create items in a warehouse depending on the number of people that arrive, you can just use an event triggered source for a persons arrival and increase that way. You can't know the number of people that will be in a place at a given time, which is why you use a statistical distribution so you can get an idea of something that would simulate reality. Could you upload an example model of something similar to what you are trying to accomplish?

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Answer 1 · 2019-11-06T08:39:41Z

Joerg Vogel answered Nov 06 2019 at 8:39 AM Brenton King commented Dec 13 2019 at 10:29 PM

You can't predict any random values. You can create a list or array of random values. Whenever You pull a value from the list, you push simultaneously a new value to the list. Because you know the entries of the list you can estimate the next events in the future.

A User Command evaluates a Global Variable string containing a statistical distribution and create an array of 10 values. The user command pulls from the global variable array the first value and push a new value to the end. 2 model triggers fill the array OnModelOpen and OnModelReset with 10 values hard coded.

initial-rand-values-global-variables.fsm

initial-rand-values-global-variables.fsm (18.1 KiB)

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