Many problem areas (like vehicle routing, hub location, ...) have certain "classic" benchmark instances that are used heavily in the literature to compare the numerical strength of optimisation algorithms.
While this increases comparability of different algorithms, it also increases the danger of tailoring the algorithms (subconsciously, often) to the benchmark instances. A read a lot of hub location papers, and most of them test on the Australian post data (besides a few other sets, like the CAB set). This means that you cannot know whether the numerical results would still hold on instances with a different structure.
What can be done to solve this problem? I am looking for approaches from the literature that try to reduce this "overfitting" problem.
To make this clear: This is not meant as a rant or open discussion, but as a question for concrete, usable approaches.