. optimization
Given that optimizing is reasonable, compile in full optimize mode and run your program on "real-world" input data. If you don't have access to real input data, choose your test input data with care: programmers tend to test with a smaller set of input data and a different variety of cases than the the program will likely encounter once it's in the hands of users.
Once you have identified a bottleneck, for example a loop that is executed thousands of times, remember that the best thing to do is to redesign the program so that it doesn't need to execute the loop thousands of times. This is more effective than making the loop run 10% faster, yet just as often, which is precisely the sort of thing an optimizing compiler can do by itself. Optimization is simply waste of programmer time if any of these statements are true: parts of the program haven't been written yet the program is not fully tested and debugged it seems to run fast enough already .
Operations Research is characterized by its broad applicability, by it rigorous mathematical foundations, and by the wide variety of career opportunities. In the last years, the Operations Research group at DEI gained an internationally-recognized expertise on advanced techniques for solving difficult Operations Research problems, which is witnessed by 100+ publications of the group in top-level scientific journals. In particular, important optimization problems that can be modelled as Mixed-Integer Programming (MIP) problems have been addressed and solved, most of which derived from real-world applications in the field of air traffic control, vehicle routing, and telecommunications.
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