ways to solve optimization problem with cartesian product and restrictions in a production line

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I'm new to this kind of problem and I'm having a lot of difficulty in understanding how to solve this problem: let's suppose we have 3 types of objects to produce in a production line (A, B, C), I know the processing time of each onject on the production line (Pa, Pb, Pc).

the problem is quite simple I think, I want to find the optimal scheduling of daily production respecting the following constraints:

  • I have to stay within the range of 8 working hours
  • each product has a minimum daily production to be respected.

so, to give an example, let's say that I have to produce a minimum of:

  • 3 type A products
  • 2 type B products
  • 1 type C product

in 8 hours

I would like to obtain an algorithm whose output for example is:

in 8 hours the sequence of products you have to make respecting the constraints is AABBBCAAC.

now, I tried to do it with a simple Cartesian product using itertools of Python, trying to filter the solution, but for my problem the algorithm is too expensive at a computational level because I have a very high daily production of products.

I also tried to use search algorithms, but I don't quite understand how to embed constraints.

finally, I tried to formulate the problem with Mixed Integer Programming, but I don't know if there is something faster.

Can you tell me a smarter and more effective way to solve the problem? If you can give me some examples to understand better, I would be grateful.

Thank you

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