How to set the ultimate goal in experimenter?

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question

Sia Sengchoon193 asked Mar 30, '22 Ryan Clark commented Apr 5, '22

How to set the ultimate goal in experimenter?

I want to set 10,000 orders to run within 8 hours. Is there something wrong with my settings in the experimenter or with my source?

I want to set goals first and then see how my other machines are tuned

Queueing simulation_autosave.fsm

Software Version:

FlexSim 21.2.3

experimenter optimize solution

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queueing-simulation-autosave.fsm (212.1 KiB)

· 3

Ryan Clark commented · Apr 05, 2022 at 04:51 PM

Hi @Sia Sengchoon193, was Felix Möhlmann's answer helpful? If so, please click the "Accept" button at the bottom of their answer. Or if you still have questions, add a comment and we'll continue the conversation.

If we haven't heard back from you within 3 business days we'll auto-accept an answer, but you can always unaccept and comment back to reopen your question.

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Sia Sengchoon193 Ryan Clark commented · Apr 05, 2022 at 05:38 PM

sorry～i accept already

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Ryan Clark Sia Sengchoon193 commented · Apr 05, 2022 at 05:59 PM

No worries! Thanks!

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Answer 1 · 2022-03-31T06:21:05Z

Felix Möhlmann answered Mar 31, '22

I think there might a misunderstanding? The experimenter and optimizer, while bundled together in one window, are separate entities.

The experimenter allows you to run your model with different, pre-defined parameter sets (scenarios) in quick succession without having to manually reset the model and change the parameters. It only uses the values set as scenario though.

The optimizer (requires separate licence) can alter the parameters by itself (within the bounds set in the parameters table) and tries to maximize/minimize one or more objective functions. These target functions can be a single performance measure or a calculation involving multiple measures, for example a ratio.

The optimizer is run through the "Optimizer Run" tab which also has settings for the maximum amount of runs or time it is allowed to use.

Neither of the options allows you to set a target value. As written above, the experimenter only uses pre-defined parameter sets and the optimizer tries to maxmize/minimize the objective but doesn't have a "target value".

There is also a small issue in your model: The first processor (former) should first connect to a queue which then leads to the combiner. Otherwise, if mutiple formers are added, they will all have their own connection to the combiner instead of providing the boxes through port 1.

An optimizer run with 40 replications returns a maximum of around 210 per hour (limited by travel times of task executers/operator).

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