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whenever I read papers on OR that use an LP/MIP approach, they include the time solver used, as well as the version and the year. I would like to know how much faster the same experiment would be nowadays with the current advances in both hardware and software (solvers).

So for example, if an experiment was done on CPLEX 8.0 in 2012, how much faster would it be nowadays with the current CPLEX version? (knowing how hardware affects this, would be great too)

This is crucial for knowing whether I can model the program in a certain manner. I have been looking for a unified source or at least some information I could use to do a conversion. Unfortunately, I have not had any luck.

Can someone bring any light to it?

PS: It is the first time I write a post. I apologize in case the format is not the appropriate one.

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  • $\begingroup$ In addition to Brian Borchers' answer, I suggest you to check or.stackexchange.com . There may already be some similar questions over there. If you are planning to post your question there, do not just copy-paste, or at least check what their policies are. $\endgroup$ Mar 18 at 20:06
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There has been progress both in terms of the speed of computers (basically driven by Moore's law) and in the algorithms used to solve LP's and especially MILP's. Overall, improvements in algorithms have had at least as large an effect as improvements in hardware.

How this will work out for your particular model is a different question. Especially for MILP's, the performance of the solvers depends a lot on the particular model and you can't really generalize from benchmark studies.

Some papers that discuss this include:

Bixby, Robert E. "Solving real-world linear programs: A decade and more of progress." Operations research 50.1 (2002): 3-15.

Bixby, Robert, and Edward Rothberg. "Progress in computational mixed integer programming—a look back from the other side of the tipping point." Annals of Operations Research 149.1 (2007): 37-41.

Bixby, Robert E. "A brief history of linear and mixed-integer programming computation." Documenta Mathematica 2012 (2012): 107-121.

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