Best algorithm with multiple variables
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I am new to data science and have my hands full with the current scenario:
Say we have a production line and want to find the optimized combination of speeds to run the equipment, with 3 different machine speeds that we are tracking. These speeds change slightly but they have a large effect on how they interact with the machines up and downstream from each other.
My two dependent variables are waste and finished cases. I will be looking for a target that meets a minimum production requirement while giving the optimal waste:cases ratio. I am also tracking line uptime to exclude outliers from the data.
I am looking for a recommendation of an algorithm(s) to use that will help me reach my optimization goals.
python numpy pytorch
New contributor
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$begingroup$
I am new to data science and have my hands full with the current scenario:
Say we have a production line and want to find the optimized combination of speeds to run the equipment, with 3 different machine speeds that we are tracking. These speeds change slightly but they have a large effect on how they interact with the machines up and downstream from each other.
My two dependent variables are waste and finished cases. I will be looking for a target that meets a minimum production requirement while giving the optimal waste:cases ratio. I am also tracking line uptime to exclude outliers from the data.
I am looking for a recommendation of an algorithm(s) to use that will help me reach my optimization goals.
python numpy pytorch
New contributor
$endgroup$
add a comment |
$begingroup$
I am new to data science and have my hands full with the current scenario:
Say we have a production line and want to find the optimized combination of speeds to run the equipment, with 3 different machine speeds that we are tracking. These speeds change slightly but they have a large effect on how they interact with the machines up and downstream from each other.
My two dependent variables are waste and finished cases. I will be looking for a target that meets a minimum production requirement while giving the optimal waste:cases ratio. I am also tracking line uptime to exclude outliers from the data.
I am looking for a recommendation of an algorithm(s) to use that will help me reach my optimization goals.
python numpy pytorch
New contributor
$endgroup$
I am new to data science and have my hands full with the current scenario:
Say we have a production line and want to find the optimized combination of speeds to run the equipment, with 3 different machine speeds that we are tracking. These speeds change slightly but they have a large effect on how they interact with the machines up and downstream from each other.
My two dependent variables are waste and finished cases. I will be looking for a target that meets a minimum production requirement while giving the optimal waste:cases ratio. I am also tracking line uptime to exclude outliers from the data.
I am looking for a recommendation of an algorithm(s) to use that will help me reach my optimization goals.
python numpy pytorch
python numpy pytorch
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New contributor
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asked 22 mins ago
RobLowryRobLowry
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RobLowry is a new contributor. Be nice, and check out our Code of Conduct.
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