Multi crtieria alterative ranking based on mixed data types
I am happy to see that you are willing to use multiple criteria decision making tool. You can use Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), TOPSIS, VIKOR etc. Please refer relevant papers. You can also refer my papers. 
Krishnendu Mukherjee
I am building a recommender system which does Multi Criteria based ranking of car alternatives. I just need to do ranking of the alternatives in  a meaningful way. I have ways of asking user questions via a form.
Each car will be judged on the following criteria: price, size, electric/non electric, distance etc. As you can see its a mix of various data types, including ordinal, cardinal(count) and quantitative dat.
My question is as follows:

Which technique should I use for incorporating all the models into a single score Which I can rank. I looked at normalized Weighted sum model, but I have a hard time assigning weights to ordinal(ranked) data. I tried using the SMARTER approach for assigning numerical weights to ordinal data but Im not sure if it is appropriate. Please help!
After someone can help me figure out answer to finding the best ranking method, what if the best ranked alternative isnt good enough on an absolute scale? how do i check that so that enlarge the alternative set further?

3.Since the criterion mention above( price, etc) are all on different units, is there a good method to normalized mixed data types belonging to different scales? does it even make sense to do so, given that the data belongs to many different types?
any help on these problems will be greatly appreciated! Thank you!