Recommended Order of Performing Denoising, Deblurring and Super Resolution on an Image
If your image is modeled as an image which is noisy, blurry and heavily decimated the optimal thing to do is estimate the image given that model.  

The model is well defined in @Laurent Duval's answer.
I'd remark that in most real world cases the blurring is spatially variant hence it can't be modeled by convolution (Well, it is a generalized convolution).

In practice it is too hard (Was?) to solve such things and like in most cases we take the greedy approach: Step by Step.

Since most algorithms are SNR dependent, it makes sense first to handle the noise by Denoising. Pay attention that if we assume the image is blurred we have spatially correlated noise which is more tricky to deal with.

Then I'd handle the Super Resolution / Deblurring.
Since those are closely related I'd certainly solve them in one step.
Yet again, in case it is important to do them separately, start with Deblurring then Super Resolution.