Doesnt seem like anything you need deep learning for

Here let me ChatGPT this for you:

Cost Function: Since you want to create an organization chart that meets specific criteria, such as having at least one male and one female employee in each sector, you could use a custom cost function that takes these criteria into account. One option could be to penalize the model heavily for each violation of these criteria. For example, you could add a large penalty to the cost function if a sector does not have at least one male and one female employee.

Activation Function: The choice of activation function depends on the structure of your model and the specific problem you're trying to solve. Since you have a binary classification problem (assigning each worker to a sector), you could use the sigmoid activation function for the output layer to produce a probability score for each sector. The input layer and hidden layers could use the ReLU activation function, which has been shown to work well in many types of neural networks.

Setting Minimum Employees Based on Sex: You mentioned that each sector requires at least one male and one female employee. You could enforce this requirement by adding constraints to the model. For example, you could use a custom constraint that checks the number of male and female employees in each sector after each batch and enforces the requirement that each sector has at least one male and one female employee. This would ensure that your model meets the specific requirements of your problem.

Basically it's an "To do what you want to do, do what you want to do"

Yes it's more a way to exercise rather than a real necessity

What I mean is it doesn't make sense to use deep learning here.

I think you're right, not super helpful, sorry :(