First project in my second year data structures intro
Sorry, but digging in your heels or telling the students to wake the hell up is going to get you exactly nowhere. When a small percentage of your students fail to successfully complete a project it is likely their own lack of background or application. But when only about a third are able to successfully complete it, it is a problem with the course, not with them. 

Some possible reasons for the problem. Perhaps they started late on it and weren't able to do a good job as user Adam asked? If so, why was that? Are they overworked generally in your course and elsewhere? I doubt that so many are just late starters. Was it a problem of insufficient testing? Was it too many tried a brute force approach that doesn't scale? How much does the course stress that early on - both testing and scaling? It seems like they weren't able to ask questions (of the TAs at least) as the project progressed. If they get stuck, how do they get unstuck? Just on their own? 

I think you have a problem and I can't diagnose it, but you can. You can, for example, have your TAs do a postmortem with small groups. I hope you have more than one or two for 200+ students. The first question I would want the failed students to answer was "Were you surprised by the failure?" That can lead to a lot of discussion about the nature of it. I would ask about how much testing they did, especially on large sets. Were they able to use the tester effectively, providing appropriate inputs, or were they misled by it. Another question I'd want an answer to is how many students now actually know why they failed. What was it in the code or its creation that led them to failure. If they don't know that you have a serious problem going forward. I think that for these and similar questions your TAs are better able to get you usable answers. The students are less likely to feel intimidated by the questions than if you ask them directly. 

On another level, I'd ask how many independent runs did you do with each student's work? Just one? The data was random, remember. Maybe naive inputs to the tester gave them poor feedback while doing their own testing. 

Maybe a five week project with little guidance or feedback is sub-optimal. Especially if you treat it as an exam. It seems like a lot of time, until it isn't. Why not shorter projects? Why not more feedback? Why not, to be honest, continuous feedback? 

I wonder how many students who failed did so only for run time and how many weren't even able to put together an algorithm at all. Has anyone given them feedback on their code and approach other than "failed"? 

Are your expectations about what they "should have learned" in the earlier courses realistic? Are you making assumptions not warranted by the facts? 

Don't just stamp your feet. Find out why this happened and change your teaching structure accordingly. Treat it like a scientific problem with an engineering solution.