Thank you! Absolutely, the problem I'm solving is closer to the resource-constrained project scheduling problem (RCPSP) but it's also closely related to job shop scheduling.
I've mostly focused on reducing the search space so far, but I've always wondered if there's a way to significantly accelerate range queries. My B-tree map implementation is already very fast in practice, but intuitively it seems like a data structure should be able to advantage of the fact that intervals are disjoint to greatly improve performance. For example, inversion lists take advantage of disjointedness to reduce storage cost - I'd like to do the same but for performance. Many range queries also have a minimum duration requirement, so it could be useful if a data structure could take advantage of this to quickly exclude intervals during the search.
I've mostly focused on reducing the search space so far, but I've always wondered if there's a way to significantly accelerate range queries. My B-tree map implementation is already very fast in practice, but intuitively it seems like a data structure should be able to advantage of the fact that intervals are disjoint to greatly improve performance. For example, inversion lists take advantage of disjointedness to reduce storage cost - I'd like to do the same but for performance. Many range queries also have a minimum duration requirement, so it could be useful if a data structure could take advantage of this to quickly exclude intervals during the search.