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Here are a few differences I have noticed. (I am mainly an academic, but also work part-time for a consulting company that specializes in OR and AI models for supply chain and other industries.) Project Speed. The two environments operate on totally different timelines. For the most part, industry OR projects have specific deliverables with tight deadlines—...


19

My experience, as a former phd in an academic context, post doc in a semi-industrial/semi-academic context and now working for an APS editor, is the following: When working on academic problems one will typically work on well defined problems. Even though those problems will be (very) difficult they will typically not involve a lot of side constraints. On ...


18

One difference I did not see mentioned in earlier responses: moving targets. In academe, we tend to start out with a well-delineated (if perhaps overly simple) problem, and we stick with that problem. In the real world, the problem you think you are given and the problem you ultimately (hopefully) solve may not be the same. As models evolve and test cases ...


11

Just to add one more point to what @LarrySnyder610 said above about specific problem-driven projects of enterprises: Since many of industry OR problems are driven by specific use cases, some of the simplifying assumptions in academic projects are not acceptable. I don't mean the solutions to those simplified (academic) models are not applicable, but they ...


9

TL;DR version For vehicle routing problems (which is a subset of OR), academic works focus on getting the best possible solution cost for overly simplified problems, industry focuses on getting workable solutions to much more complex problems. Long version I can't comment on wider OR but I can comment on vehicle routing problems. I've worked as a CS ...


7

I only have first-hand experience of the government side, which limits my ability to compare, but since none of the other answers discuss that side of things it may be useful to have an answer from that perspective. Caveat: "government" is a large and complex beast with many different faces. My experience comes from working in a statistical agency; somebody ...


6

For having spent 10 years in Academia/OR and 20 years in the industry side of the force, I noticed that one difference is often the incremental aspect of the problem you have to solve in the industry. Imagine you want to schedule bus drivers for a city bus transit system. Most of the academic work is based on a global optimization question, with an objective ...


4

Something that has really become interesting to me is the creation of software in both of these contexts. Specifically as an end user of a commercial solver. In academia often code is written to solve a specific problem or explore potential solutions. This perhaps affords the ability to do more fundamental work. Like the exploration of how solvers work or ...


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