I work at a casino where we need to assign dealers to table games each shift. Throughout the night games close and the dealers on those closed games are used to send other dealers home on games that are opened. These can be complex situations because not all dealers are skilled equally and have all of the games.

For example, one dealer may be on a craps game and needs to go home, but the only free dealer doesn’t know know how to deal craps. In this instance multiple moves would need to be made to get the craps dealer home. I want to build an algorithm that will analyze all the open games and give recommendations on what moves can be made.

There are other different details involved such as time starts, having a relief dealer who gives others breaks, not moving dealers around too much if possible, and being able to select which dealer is to go home next.

We currently do this by hand and it is very inefficient and stressful for our managers. I’ve been learning python for the past few months but if this would be better suited for another language I’d be willing to take that on as well.

I understand this is a complex problem, just looking for some advice on what I should focus on learning next, such was what types of machine learning would be best, creating a user interface, etc. Thank you!

I have looked into bipartite matching and graphing as possible solutions but unsure how to implement it