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I am working on my MSc thesis right now which is in resource economics, but I have ended up actually operating mostly in the realm of OR and learning about programming, algorithms, optimization problems, some complexity theory, and a bit of machine learning, and I find it all pretty interesting. My thesis project is more or less an application of OR on a particular real world application, but I enjoy it and I think that it could potentially be a fun field to pursue.

However, I am curious what research in OR is actually like as opposed to simply applying OR concepts and techniques to a particular problem. With that being said, what are some areas that OR scientists actually do research in? What are some current topics currently being worked on and why, and is OR research more about developing algorithms to solve things like MINLPs or is it more about application?

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  • $\begingroup$ A search on the main site turned up this tidbit. You might be able to refine that search and turn up something on an SE site, unfortunately SO results overwhelm the returned hits. Searching our Meta using the scope tag should have turned up an answer, but sadly it does not. $\endgroup$ – Rob Oct 19 at 23:17
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Disclaimer: the following is doomed not to be comprehensive. (I'm still cautiously optimistic about it being at least somewhat correct.)

Some OR research is devoted to theory: proving that some problem is NP-weird, finding worst case bounds on either computation time or the gap between achieved solution and optimal solution for some algorithm, and so on.

Some OR research is devoted to developing (or refining) algorithms applicable to OR problems. So people may work on things like figuring out facet defining cuts for specific combinatorial problems, or accelerating convergence of data fitting algorithms, or concocting new metaheuristics. This intersects with my "theory" category; figuring out where the boundary is is left to the reader as an exercise.

Some OR research is devoted to application. Here what makes it research (as opposed to just solving something) may be applying an OR framework to a problem not previously recognized as fitting it, or finding a non-obvious model for a problem, or finding heuristics specific to a particular problem or problem class. In some cases just identifying the problem and formulating a model may be novel enough to be considered research.

As far as current topics, (a) they vary depending on which category you're looking at and (b) to borrow from Shakespeare, there are more topics in heaven and earth than are dreamt of in my philosophy. A good way to identify current topics (give or take having any idea what the terminology means) is to look at the program of a relevant conference. INFORMS maintains a calendar of both past and future meetings. You can look for recent past conferences, drill down to the program for one, and have a look at what was presented. Fair warning: if you grab a national conference without having a pretty good idea what sorts of papers you are looking for (e.g., healthcare applications), you will drown quickly. So you might want to look at a regional or specialty conference first.

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