How to work with teammates who shoot down ideas in order to avoid work?
Are you sure you are not prematurely optimizing?

You have stated that your algorithm is "very slow" and your data model is "not very efficient".  However, it is not clear that these inefficiencies will actually prevent you from delivering the main goals of your project.  You have a worry that you will not be able to scale to the necessary data size, which is a legitimate worry, but not proven at this stage.  It may turn out to be no problem.

Your colleagues' excuse-making--incorrectly claiming that solutions won't work or don't exist--is certainly unhelpful.  Nevertheless, they may be correct that these ideas are not worth pursuing.  Working on performance improvements that are not necessary to deliver the project may be a distraction from meeting the important goals.

Step one: determine for sure whether optimization is critical to the project.

Your worry about scaling to the full dataset is legitimate and important. What you should do about that worry is test on a full size dataset, as soon as possible.  If you don't have access to the real dataset yet, then make your own test data, by copying the experimental data 100 times, randomly generating data, or whatever works.

Also consider other ways that the performance may have an impact on meeting project goals, and test where it makes sense.

Step two: if appropriate, make a case for optimization on the basis of it helping deliver the project.

If you can show that improving performance is either necessary to meet your goals, or has a benefit that outweighs the cost, then make this argument.  Back up your argument with evidence (like test results).

Start with your colleagues, and if they are not convinced than discuss it with your supervisor.

However, only do this if truly necessary--and one month from your end date, you should probably only be worrying about things that are absolutely critical to completing the project.