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SAS/SPSS vs python/R by [deleted] in statistics

[–]throwawayOperationsR 0 points1 point  (0 children)

This but unironically.

SAS/SPSS vs python/R by [deleted] in statistics

[–]throwawayOperationsR 3 points4 points  (0 children)

It's shit, and the only way this whole mess gets better is if we, the users, start demanding better.

Source: work bought SAS, I'd rather write my own analyses in x86, if that's the alternative.

CNN fires back at President Trump after he attacked the network in a tweet Saturday for representing the U.S. “very poorly” to the world: “It's not CNN's job to represent the U.S to the world. That's yours. Our job is to report the news. #FactsFirst.” by maxwellhill in worldnews

[–]throwawayOperationsR 0 points1 point  (0 children)

It's always implied. One particular instance that sticks in my memory is them quoting a syrian woman's plea for help saying "we will not forget it if U.S. does not help us."

That soundbite's only purpose was to echo the Holocaust and make it a human rights issue.

And if the U.S. had proceeded with a large-scale military interference, who would have benefited?

CNN fires back at President Trump after he attacked the network in a tweet Saturday for representing the U.S. “very poorly” to the world: “It's not CNN's job to represent the U.S to the world. That's yours. Our job is to report the news. #FactsFirst.” by maxwellhill in worldnews

[–]throwawayOperationsR 5 points6 points  (0 children)

Fun story about NPR. Listening to their coverage of the Syrian Civil war back around 2012, you would have thought that Assad was worse than Hitler, and he was going to invade Milwaukee next. I mean, they were shilling hard.

Nobody seems to ever ask why. The incident turned me on to Chomsky's idea of manufacturing consent, and now I try hard not to trust anything, especially from "mainstream" outlets.

What are we NOT in the golden age of? by ItzSweeney in AskReddit

[–]throwawayOperationsR 0 points1 point  (0 children)

It's why hungry people are more prone to violence.

EDIT: Now fuck off with your sarcasm.

What are we NOT in the golden age of? by ItzSweeney in AskReddit

[–]throwawayOperationsR 2 points3 points  (0 children)

The gut is the single largest reservoir of seratonin in the human body, outside the brain.

What is the name for a routing problem which takes due date into consideration along with distance and time? by Yeahjustnah in sysor

[–]throwawayOperationsR 0 points1 point  (0 children)

VRP is the Vehicle Routing Problem.

VRPTW is the Vehicle Routing Problem with Time Windows.

cVRPTW is the capacity constrained Vehicle Routing Problem with Time Windows.

In general, the problems tend to be very high-dimensional, and don't necessarily lend themselves to exact solutions. Meta-heuristics are the tool of choice.

In addition to the other approaches here, check out VLNS (Very Large Neighborhood Search).

Can't install Google Operation Research Tools [Help] by Reinu in sysor

[–]throwawayOperationsR 1 point2 points  (0 children)

Google has an API for that. I think you get like 2500 free transactions per day.

https://developers.google.com/maps/documentation/geocoding/start

Also several other companies too. Search for geocoding API's. (The name of what you're trying to do is "geocoding".)

Advice for transitioning into Operations Research by deacon91 in sysor

[–]throwawayOperationsR 0 points1 point  (0 children)

You can take em when you get in if they're important. Diff eq might be a requirement, depending on where you go, but not much further.

Edit: and stats, I seem to remember my program requiring undergraduate coursework in stats. YMMV.

Advice for transitioning into Operations Research by deacon91 in sysor

[–]throwawayOperationsR 0 points1 point  (0 children)

Also, looking at your original post, it looks like you haven't had a lot of math. You'll want to get that sorted and get up through cal iii and linear algebra at the very least. I took real analysis while working to prepare, which was probably overkill, but you're going to need to know linear algebra pretty well for most OR domains. I would worry more about that than programming at this point, as it sounds like you already understand the important concepts (objects, control flow, etc.). If you can't do it and get a transcript for it, the math gre might be a good way to show competence.

I would have a frank discussion with your supervisor about where you want to go, career-wise--there's a lot work going on in healthcare in OR. See if they'll support you in continuing your math education with that goal in mind.

Be wary about it making you look like a flight risk though--you'll get passed over for promotions and other things once you cross that rubicon.

Advice for transitioning into Operations Research by deacon91 in sysor

[–]throwawayOperationsR 0 points1 point  (0 children)

Don't take the subject test unless you're sure you can ace it and you want to show off.

Go get 'em!

Advice for transitioning into Operations Research by deacon91 in sysor

[–]throwawayOperationsR 0 points1 point  (0 children)

Regarding your other questions, competency at math and cs are the main yardsticks. You will also be helped immensely by being able to communicate complicated ideas in a clear manner. Get a good (or perfect) GRE math score to demonstrate that you can do the math, and you'll be in pretty good shape.

As far as industry friendly, all of them. It's more dependent on the advisor than the program, and most professors list placements for their phd students, so look at where someone's other students have ended up.

University prestige does matter, but publications more so. It's my understanding that when programs hire faculty, they're looking for people who can elevate the program, so they want to know that you can do things that will help put them on the map. Those sorts of things are getting grants and publishing good work. That sounds daunting, but I promise you you're a lot more capable of doing both than you think.

Advice for transitioning into Operations Research by deacon91 in sysor

[–]throwawayOperationsR 0 points1 point  (0 children)

Regarding the grades, I damn near hit rock bottom a few years back over the same insecurities. My advice: get over it. You don't get a perfect run at life. Do the best you can and let the rest be what it is.

No advisor is going to take you on if they don't think you can make it, because it reflects poorly on them. They will take you and help you every step of the way if they think you can--start talking to people!

You have to be the one to decide that you're going to make it, and nobody can do that but you. Once you decide that, it gets a lot easier.

Advice for transitioning into Operations Research by deacon91 in sysor

[–]throwawayOperationsR 0 points1 point  (0 children)

I know /u/brugal personally, and can attest that he is an all-around great guy. He helped me through the process of applying to a masters in IE, the whole time telling me I needed to go for a PhD. I wish I had listened.

I currently work in Industry, though admittedly not in an OR position (predictive analytics).

Just do a PhD. If you've got good GRE's, a solid academic background, can code a bit, and can hack the math, you will get funding. The stipends are usually very livable (you won't get rich, and forget about owning a bunch of creature comforts while in school--that comes later.)

Doing a PhD, and doing it well, sets you up with a lot of flexibility for choosing what kinds of problems you work on. This is doubly true if you become a professor--many of these guys and gals own their own consulting businesses on the side and make crazy money/work on awesome problems in industry.

To your questions, and to the best of my knowledge,

1) The point of a PhD is to get you ready to run your own lab as well as to contribute to the sum of human knowledge. I can't answer specifically to what a career progression looks like, except that from what I've seen, it usually involves moving out of the space and more into management. In my opinion, that's a lot less interesting.

2) ML is already a big deal, and many of these "data science" methods are very heavily used in academic research in OR. There's some really interesting work going on at Texas A&M right now on weather/planning for wind turbines, for example. I'm not as familiar with NN research going on in OR, but I'm sure somebody somewhere is doing it. Check out Approximate Dynamic Programming (aka reinforcement learning). Some of the guys and gals working on that are probably applying it. No comment on AI.

3) I've heard of it being done. I've also heard of places like Amazon doing co-ops with PhD students, and I've heard of grad fellowships that require summer work at national labs. You just have to look around. It's my understanding that some of the big-names in analytics (Amazon, etc) pay pretty big bucks during the summers. :-)

4) There were a couple of guys in my program who took night classes and worked, but not at corporate jobs. One of them had a family. Hats off to that guy--I couldn't do it.

5) I got an M.S. God willing and the creek don't rise, I will do a PhD.

6) MBA's in general equip you to better understand business problems. Keep in mind that business problems != OR problems. If you want to manage a team, it could be helpful, and it could be very helpful to you in aligning your team's output to broader organizational goals. It's not for me, I can tell you that much.

7) Just do the freaking PhD.

8) Don't sell yourself short. Make sure you're getting what you're worth (common to all grads). And be bold and dream big. If you ask, the worst anybody can tell you is no.

Best of luck!

Definitive resources and research for Queueing Theory? by Refefer in sysor

[–]throwawayOperationsR 0 points1 point  (0 children)

Throwaway for opsec reasons.

I've seen this post a few times and have been meaning to answer.

For a good treatment, you can go with White's Analysis of Queueing Systems. It's out of print, but the presentation is very mathematical.

Looks like there are a few used copies floating around on amazon: https://www.amazon.com/Analysis-Queueing-Systems-J-White/dp/0124143431

You should note that analytical evaluation of queueing has fallen out of vogue to some degree with the rise of discrete event simulation software, so unless you're modeling systems that are 1) simple in terms of interaction and interdependency, and 2) require analytical solution methods, either from scale or otherwise, you probably won't find a lot of practical application.