With a sufficient population size, taking advantage of better sampling techniques for initial population generation can make a significant difference. I've used LHS and modified LHS approaches before, but I wanted to keep things simple, at least in the earlier parts of the book!
Something I've worked on with a colleague recently is using a more data science with pre-optimisation exploration (https://link.springer.com/chapter/10.1007/978-3-030-43722-0_...), hoping to do more work on this soon. With regards to high dimensionality in the search space, this kind of approach could be useful.
Previously I've been more interested in high-dimensional objective space and how to deal with them, primarily using progressive preference articulation.
If you have any requests for additional sections in the book I would love to hear them! Something high up on my list is doing a section or two on my neuroevolution algorithm, but keeping it at the right level is tricky.