# A deep learning algorithm to optimize the outcome

I'm am quite new to deep learning but I think I found just the right real-world situation to start using it. The problem is that I have only used such algorithms to predict outcomes. For my new project, I need information to feed a machine with to optimize outcomes. Could someone explain briefly how I should proceed? I'm stuck.

Here's the situation:

I have a machine that takes planks of wood with different grades of wood available throughout its length and has to cut it into blocks provided in a cut list. This machine will always choose the highest score it can get from a given plank. The score is obtained by multiplying each block's area by its multiplicator. The algorithm I want to build has to give that machine a multiplicator for each block listed in a cut list. All of the physical output from this machine will be stocked on shelves by a robot until needed. The cutting machine is allowed to downgrade parts of a plank if it helps it reach a higher score.

The value has to act as an incentive for the machine to give me the block I need the most without downgrading too much wood.

OPTIMIZATION GOALS

• Make sure each block is in stock by the time it is needed, but not too early without reason
• Downgrade as little area of wood as possible (some species are very expensive)

INPUT NODES

• Amount of time before this block is needed
• Grade of wood for this block
• Amount of this block needed
• Block's area (Maybe?)

FEEDBACK PROVIDED TO THE ALGORITHM

• Amount of time in advance that the block was ready (must be as low as possible)

EXPECTED RETURN DATA

• A multiplicator that will give that block an optimal its priority relative to others

INFORMATION I DON'T HAVE BUT COULD GATHER

• Mean ratio of each grade for each species of wood

What I've figured out so far is that I may need my feedback to be smashed in only one value in order to make it the output node. The problem is that I can't understand how to make this algorithm to determine a multiplicator. Am I wrong in trying to solve this through deep learning?

• I took the liberty of editing the question for more clarity. Wasn't sure what to do with: "Value per cm² that will give that block an optimal its priority relative to others" Do you mean giving a block an optimal value in regard to its priority relative to other blocks? Aug 31, 2017 at 20:09
• @DukeZhou The machine's algorithm multiplies the value i'm trying to optimise by the total 2D area of the block (width x length) in order to create a "score" and cut each plank to get the maximum score. If I ass the block's area in the algorithm, I could then determine the score and then divide it by the area. All in all, the main focus is in making sure that the highest score matches the highest need so that the machine's goal is the same as ours. Aug 31, 2017 at 20:41
• @DukeZhou Sorry if it ain't as clear as it could, English is my second language. Aug 31, 2017 at 20:42
• Good info. You should edit that one line I referenced to make it more clear, and check my edit to make sure I didn't misrepresent any part of your question. Aug 31, 2017 at 20:43
• @DukeZhou Here. I replaced it with the term multiplicator and gave some extra information about its usage. Aug 31, 2017 at 20:56