It would have to be two conditions, that and no new cards left either.
@L.M.Sherlock So I have a few things that I see that (I think) need to be changed on the sim and it’s no longer relevant to this discussion. Should I create a new thread on the anki forum, or is there another place you’d prefer I do that, like on github itself? I don’t have a github, so I’m new to that.
You can open an issue on Github: GitHub - open-spaced-repetition/review-sort-order-comparison
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Oh yeah, check out how slowly due_date_asc is going through that backlog after the new cards ran out. The whole sim is going to take a while, but I can already see this will make a huge difference.
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Ok, so here’s two to compare. This is gonna take forever and I’m going to leave and let it sit. I’ll post all the results later.
I lied. I stopped the sim and just ran PRL because I wanted to see it now:
Ok, now I’m leaving and letting it run them all.
What sorting method are you testing here
It says under the last day for each one, when it gives the final stats.
It seems to confirm that Retrievability Descending is best sorting method overall.
No, I think it’s confirming PRL is. Retrievability Descending takes the longest of those three.
Did you include the changes you wanted to do earlier (making the simulation run for longer) 
Yeah, this is running the sim until there’s no backlog. So, on the last day your 80 reviews covers every review you have left to study that day.
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Ah great! But it is still hard to determine a clear winner here. What does PRL stand for btw and is it hard to add to Anki as a sorting method
Dae has already added the inclusion of Reverse Relative Overdueness to the next as an issue on Github.
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Potential Retrievability Loss (PRL) = R(Today) - R(Tomorrow)
I think total time represents a good winner. Total minutes of studying time it took to completely learn all your cards and get through your backlog.
Alright, I did it the dumb way - let’s add 1000 to learn_span and just look the graph, without finding the exact day when average true retention matched desired retention. The problem is that the graph has 16 curves, which makes it hard to tell what’s going on
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Kinda weird that difficulty_asc plummets in True Retention per Day as soon as you run out of new cards.
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I was worried about Difficulty Ascending because Difficulty is not dynamic (changing with days passed) like Retrievability (on which PRL and Retrievability Descending obviously depend).
Maybe that has an influence.
It appears that in your simulations Retrievability Descending also remains to be the winner.
@rich70521 the weird plummet of Difficulty Ascending is also consistent in Expertiums simmulations.