Bobyqa error message help

[Schisto]

I don't know what the
convergence code 3 from bobyqa: bobyqa -- a trust region step failed to reduce qData: Data3 error message means. Should I be concerned about this error? See below for example:

I using backwards elimination to get the minimally significant lmer model.
My model comes up with an error that says:
boundary (singular) fit: see ?isSingular
I have done some research and I believe this error to be fine as individual child should be included as a random effect in the lmer model.

I compare two models

cca_p <= lmer ( A ~ B + C + D + E + (1|child), data = Data)

# remove E (as least significant main effect from model)
cca_p1 <= lmer ( A ~ B + C + D +  (1|child), data = Data)

# compare the two models to determine if E is significantly important to the model.
anova (cca_p, cca_p1, test = "Chisq")

I then receive this output but do not understand what the convergence code 3 from bobyqa error message means:

Googling suggests that re-leveling my data alters this. Sure enough if I relevel some of my data the error will go away but reappear later on in the modelling.
Secondly the error will vanish depending on the order I remove the explanatory variables but I should really remove the least significant ones first rather than remove them in an order that doesn't give me the error message.

I then tried the following to determine which optimizer I should be using if not bobyqa:

and also allfit

I am assuming that it is something to do with the singular fit but I'm not sure. Should I be concerned about this or is it okay? I can backwards eliminate with this error and get a final minimal model from it if I ignore this but I am not sure if I should be ignoring it.

Any advice greatly appreciated.

[nirgrahamuk]

Personally I wouldnt be typically satisfied with model fits that complained of singularity, because I'd be looking for robust models (not overfit) and If I'm doing something scientific I might like to learn something from the coefficients, and so, I'd probably trade of accuracy for generalisability, and address the causes of singularity.

I just like to say, that I have no context for what you are doing, and what is important to you, so all advice should be taken with more than a grain of salt