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For questions asking for references from the literature or textbooks on specific topics.

8
votes
Optimization is a very large area in terms of the types of problems and models. You have taken a course on linear programming, in which (a) the problem is deterministic (you assume that you know at th …
answered May 23 '21 by prubin
2
votes
You might look at the following (largely INFORMS stuff). The archive of past winners of the Franz Edelman Award. OR/MS Today, OR/MS Tomorrow (the student-oriented analogy of OR/MS Today) and Analytic …
answered Jan 12 by prubin
6
votes
There's an old joke (popular at least in New York, back in the day). Newly arrived tourist to local: "How do I get to Carnegie Hall?" Local to tourist: "Practice, practice, practice." I can't say how …
answered Sep 9 '19 by prubin
4
votes
You can find all the necessary theoretical elements (and a lot more) in the book "Convex Analysis" by R. Tyrrell Rockafellar. Fair warning: reading this book is tantamount to a graduate class in conve …
answered Sep 29 '21 by prubin
2
votes
I'm not sure I would use the word "standard", but a common practice is to scale the goals so that they are commensurable. There are also multiobjective approaches that are less affected by scaling. Fo …
answered Dec 10 '21 by prubin
5
votes
I checked with a colleague who taught procurement / sourcing / purchasing / supply management / for quite a few years. He's skeptical about there being any heavily OR-oriented books in the field. Tha …
answered Sep 1 '20 by prubin
14
votes
There are multiple levels to operations research. (Before continuing, I want to apologize to anyone about to be scandalized by my omission of their favorite journals.) For some (many?) people workin …
answered Feb 9 '20 by prubin
11
votes
Since you mentioned videos, I would suggest checking Coursera and edX for free MOOCs (such as the Deterministic Optimization course on edX or the Discrete Optimization course on Coursera). The Courser …
answered Aug 18 '19 by prubin
13
votes
The implementation gap may not be a function of the "quality of the model" (or the algorithm used to solve it, which is a separate dimension). I had an experience with a logistics problem where the mo …
answered Dec 19 '19 by prubin
8
votes
It's not exactly the same thing, but very close: in goal programming, using a weighted combination of the deviations from goals is often called "Archimedean" (as in "Archimedean" goal programming, or …
answered Jun 5 '19 by prubin
8
votes
Here's an answer (from 2018) by one of IBM's CPLEX specialists: "Citing CPLEX".
answered Sep 25 '19 by prubin
10
votes
What I'm about to suggest is less sophisticated than (and presumably less efficient than) the presolvers Mark L. Stone mentions, but would be relatively easy to implement (assuming you have an LP solv …
answered Dec 7 '20 by prubin
18
votes
Your examples of "technical skills" are centered on optimization. An understanding of at least some aspects of probability models (especially Markov chains and queues) may be important, depending on t …
answered Oct 28 '19 by prubin
4
votes
There's not much documentation (and no literature), and the applications are pretty basic, but you can find blurbs on several projects with nonprofits at the INFORMS Pro Bono Analytics "Our Work" page …
answered May 18 '20 by prubin
3
votes
I would say that a "best bound" (lower bound if you are minimizing) has essentially the same role regardless of whether the method is exact or approximate: to give you an idea of how close to optimal …
answered Jan 6 by prubin

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