<p>I need to implement a policy gradient algorithms (actor-critic) for the 2D cutting stock problem with varied size stocks. However I'm new to machine learning so I still have no clue how to design the policy.</p>
<ul>
<li>There are 25 product type, each has demand at most 20.</li>
<li>There are 100 stocks, each stock is represented as a 100 by 100 grid. Each grid element is either -2 (not in stock), -1 (in a stock), or a non-negative integer (the index of the product placed on the stock)</li>
</ul>
<p>Thank you!</p>

CC BY-SA 4.0
2024-12-05T11:05:13.947Z
Ok, can you provide a brief description of the problem and what the goal is? Thanks for providing already some info about the problem but you're not explaining what the goal is.
nbro
CC BY-SA 4.0
2024-12-07T14:16:04.853Z
Hello nbro! The goal is to minimize the trim loss, or minimize the total waste area of the stock used!
Phạm Trần Minh Trí
<neural-networks><reinforcement-learning><policy-gradients><actor-critic-methods><reinforce>
Model the Policy for policy gradient for the 2D cutting stock problem
Phạm Trần Minh Trí
# Model the Policy for policy gradient for the 2D cutting stock problem

(Asked by: username_0 on 2024-12-04)

I need to implement a policy gradient algorithms (actor-critic) for the 2D cutting stock problem with varied size stocks. However I'm new to machine learning so I still have no clue how to design the policy.

* There are 25 product type, each has demand at most 20.
* There are 100 stocks, each stock is represented as a 100 by 100 grid. Each grid element is either -2 (not in stock), -1 (in a stock), or a non-negative integer (the index of the product placed on the stock)

Thank you!

**Tags:** neural-networks, reinforcement-learning, policy-gradients, actor-critic-methods, reinforce

> **Comments:**
> **username_1**: Ok, can you provide a brief description of the problem and what the goal is? Thanks for providing already some info about the problem but you're not explaining what the goal is.  
> **username_0**: Hello username_1! The goal is to minimize the trim loss, or minimize the total waste area of the stock used!  

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## 0 answers

