Is there any mathematical result that states that the Wilcoxon-Mann-Whitney (WMW) test is optimal in some sense, for a specific testing problem that is a subproblem of the general problem the WMW test is testing, say against an alternative of two specific distributions where one is stochastically larger than the other, maybe a location shift model with specified distributions but maybe something else? I have in mind maximum power for given level, however I'd be interested in other types of optimality as well. Also I suspect that any result would be asymptotic, maybe of the type "locally asymptotically optimal".
I had a look at the Hajek, Sidak, Sen book Theory of Rank Tests, but I don't think it has such a result. There is an exercise that states efficiency 1 of the Wilcoxon signed rank test for one sample in a specific situation, also mentioned here: https://www.jstor.org/stable/43686636
I am however not aware of anything like this for the two-sample test, and I'd like to know whether anything exists.