I believe your options 1 and 2 could be equivalent once you code the data. I think in either case you're tricking the designer to get the result you want, which is two five-level variables which never appear together and which will be coded with 4 effects-coded variables each. It is this reality you will need to test and I think to do so you may need to run the model in CBC/HB with artificial data (whereupon I suspect you will find the two to be equivalent).
So the design you have generate in SSI Web's CBC designer needs to be recoded to capture your model and analyzing the recoded design will be a bit of (probably unnecessary) work for you.
Your third design alternative, partial profile, probably is not a solution for your problem. However, I do want to point out that people misunderstand the value of partial profile designs - such designs do not (and cannot) compete with full profile designs in terms of statistical efficiency. Their big benefit is in simplifying designs with many attributes and reducing respondent error, thus increasing respondent efficiency and improving total efficiency (but not, again, statistical efficiency).