The BBC and queues

The BBC has an economics editor named Evan Davis who has a blog on understanding the real world using the tool kit of economics. There are two recent entries (here and here) on queueing results. Now the English are famous for their queueing discipline, but Davis is concerned with two examples of “non-obvious” queues: road congestion and waits for health services. In both cases, there are significant costs to queueing and the economic effect is that since people enter the queue only when the benefit of the service outways the cost of queueing, many people end up with very little value (the queue increases to wipe away the consumer surplus). This is a nice example of combining economics with operations research (many OR models have very simple queue entry rules, like “will enter always” or “will enter only if queue size <=12"), but using economics to guide the consumer behavior leads to better insights. Davis shows his economist (not OR!) training in stating the following:

There are three very simple rules about queues.

• 1. They grow longer when the number of people joining at the back of the queue exceeds the rate at which people are being dealt with at the front.

• 2. They grow shorter when the rate at which people are dealt with at the front exceeds the rate at which people join at the back.

• 3. They stay constant when the flow of new arrivals is equal to the flow of people being seen.

It is the last point that is incorrect, assuming there is any variation at all in either service or queue entry. If flow of arrivals equals flow of people being seen, the queue will continue to increase (on average). This point is actually very important. Managers are constantly being told to look for inefficiencies, and having more service than customers looks like an inefficiency, so they work at getting service = customers. The result is long queues (unless there is no variation in service or queue entry). Unless there is slack in the system, the system doesn’t work.

Davis does mention Operations Research (surprisingly: Operational Research would be more “british”):

Queuing theory is in fact, quite a science. It comes up in the discipline of Operations Research, which studies processes, production and organisations using maths, statistics, economics and management science. It’s a fascinating subject.

The “It’s” in the last sentance is unclear. I’ll take it to mean that “Operations Research is a fascinating subject”, which is certainly the case.

MIT Conference on Sports Business

MIT is holding a conference this weekend on Sports Business (unfortunately it is sold out) with a focus on Analytical Sports Management. This workshop is an interesting mix of sports insiders, economists, operations researchers, media executives and more, with a strong emphasis on those in the business. No talks directly on scheduling (my particular emphasis) but a cool looking conference nonetheless.

Brenda Dietrich in Fast Company

Brenda Dietrich,  President of INFORMS and head of Math Sciences at IBM Watson Research is profiled in Fast Company this month.  Some wonderful stories:

If you’re not a mathematician, the deep math that Dietrich and her team perform sounds utterly foreign–combinatorial auctions, integer programming, conditional logic, and so on. Their whiteboard scribbles at Watson look incomprehensible, like Farsi or Greek (then again, many of the symbols are Greek). But these mysterious equations represent the real world and how it works. When mathematicians “model” a problem, they’re creating a numerical snapshot of a dynamic system and its variables.

Take the forest-fire project Dietrich and the researchers are working on. Extinguishing fast-spreading flames over tens of thousands of acres is an expensive and complicated undertaking. In 2000, a particularly devastating year, the federal government spent more than $1 billion and still lost more then 8 million acres. Its fire planners want to reduce the cost and the damage through better coordination among the five agencies involved.

Armed with seven years of data, IBM’s mathematicians are creating an enormous model that shows how the resources–every firefighter, truck, plane, etc.–have been used in the past, how much each effort cost, and how many acres burned. The algorithms describe the likely costs and results for any number of strategies to combat a given fire. “How many bulldozers and buckets do you keep in Yellowstone Park?” Dietrich asks. “And if you need to move them elsewhere, how much will it cost and how long will it take?” She’s talking fast, describing the unruly variables that math makes sense of. “It’s a nice project. Complicated, huh?”

It is too bad that Brenda is described as a mathematician (which she is) rather than the more specific and accurate “Operations Researcher”.

Do Operations Research, win $1 million

Art Geoffrion wrote me, pointing out that the Netflix Prize is a great opportunity for OR people to show their stuff. Netflix is offering up to $1 million for a system that predicts whether a customer will like a movie or not. They have made available a wonderful database of 100,000 ratings. Lots of people have used data mining methods on this database For me, the line between data mining and OR is very thin indeed, so it would be interesting to see what an OR approach can do with this.

The Wall Street Journal has an article on these types of prizes. There are a lot of good reasons for companies to provide these competitions:

Prizes prompt a lot of effort, far more than any sponsor could devote itself, but they generally pay only for success. That’s “an important piece of shifting risk from inside the walls of the company and moving it out to the solver community,” says Jill Panetta, InnoCentive’s chief scientific officer. Competitors for the $10 million prize for the space vehicle spent 10 times that amount trying to win it.

Contests also are a mechanism to tap scientific knowledge that’s widely dispersed geographically, and not always in obvious places. Since posting its algorithm bounty in October, Netflix has drawn 15,000 entrants from 126 countries. The leading team is from Budapest University of Technology and Economics.

Given the generality of OR, it is clear that our field can be competitive in many of these. Any takers?

Quant at Barclay’s Global Investors

Business Week has an article on how Barclay’s Global Investors has hireed more than 100 Ph.D.s in quantitative areas to define its investment strategies. The article discusses the advantages of quantitative investing:

In traditional circles, quant has been derided as “black box” investing for its reliance on computer models comprehensible only to the double-domes who created them. The black box survives today in the more mystifying form of investing techniques derived from fuzzy logic, neural networks, Markov chains, and other nonlinear probability models.

As epitomized by BGI, though, modern quant investing is grounded in the same economic fundamentals that preoccupy mainstream analysts, though quants amass much more data and massage it more systematically than anyone else does. Another key difference is that quants ignore the story behind the numbers. The whole sprawling human drama of business is of no interest to Barclays researchers, who never venture out to call on a company or tour a store or a factory. If a thing cannot be measured and factored into an investment hypothesis for testing against historical data, BGI has no use for it.

Quants also are far more mindful of risk, as measured mainly by price volatility. Traditional portfolio managers tend to heighten risk by concentrating their investments in a relative handful of companies that they believe will beat the market averages over the long run. Instead of angling to get in early on the next Wal-Mart (WMT )or Microsoft (MSFT ), BGI spreads its bets across a broad market swath, frequently trading in and out to exploit small pricing anomalies. The firm’s $19.9 billion in alpha represents just 1.64% above the market return, on average.

It is in a discussion of a presentation by one of the researchers, Xiaowi Li, that it is clear the breadth of skills that can go into this sort of work:

Gathered around a table in a small conference room on the 28th floor of BGI headquarters were a half-dozen of Li’s peers, plus her manager and the co-heads of the overall Asian research effort, Ernie Chow and Jonathan Howe, both of whom joined BGI in 1999 and were the fortysomething graybeards of the group. Everyone in the room had either a PhD or a master’s degree in financial engineering. The disciplines represented included physics, applied mathematics, and operations research, as well as finance and economics.

Nice to see operations research mentioned without need for further definition.

Death of Peter Hammer

Peter HammerIt is with great sadness that I pass along news of the death of Peter Hammer. Here is the announcement I received from Endre Boros:

It is with deep sorrow that I have to inform you of the tragic death in a car accident of Professor Peter L. Hammer on December 27, 2006. His wife Anca, the only other passenger in the car, is recovering from minor injuries.

Below is information on the funeral for Dr. Hammer.

The funeral will take place on Sunday, December 31, 2006, at 1pm. The location is the Princeton Cemetery (29 Greenview Ave Princeton, NJ 08542) .

Telegraphs or cards can be sent to the family (wife Anca, and sons Alex and Max) at 19 Littlebrook Road North, Princeton, NJ 08540-4063.

Flowers can be sent to the Princeton Cemetery, 29 Greenview Ave Princeton,
NJ 08542.

Directions to the Princeton Cemetery: From Nassau Street (the main street of Princeton, State Rt. 27) turn onto Vandeventer Avenue (opposite to Washington Avenue), after 0.2 mi (at the end of Vandeventer) turn left on Wiggins Street, and then immediately (128ft) right onto Greenview Avenue.

Peter has been an amazing force in our field, and an inspiration to all of us. His passing is a tremendous blow, both personally, and to the field.

Added January 4

Rutcor has a page on Prof. Hammer.  It includes the following:

His family collects stories, facts, thoughts, feelings, and even rumors about Peter L. Hammer. Please email your comments to: maximhammer@yahoo.com.

Contribution in His Memory may be made to:

Post-Polio Health International (PHI)
4207 Lindell Boulevard
St. Louis, Missouri 63108-2915
USA

either by writing a check to Post-Polio Health International or directly through their website http://www.post-polio.org/don-mem.html

Please, kindly mention “In Memory of Peter Hammer”.

OR Takes Over …

… the University of Delaware, at least. Pat Harker, former editor of Operations Research and plenary speaker at this year’s INFORMS conference, has been selected as President of the University of Delaware. Interesting career trajectory: OR faculty to Dean of Wharton to university President. And he is only 48! Being 46 myself, I console myself thinking “if only I hadn’t given him a two year headstart”. Congrats, Pat!

It is great to hear from you but…

It is great to hear from people out there interested in OR, but there are a couple types of email that I don’t like to get. I think lots of faculty have the same peeves. Jeffrey Ullman of Stanford (founder of much of database theory) has a nice page on this, which I will essentially copy here:

One class of email can be summarized as follows: “You don’t know me, but I have the following credentials and I would like you to arrange for me to be admitted to Stanford, in preference to someone with equally good or even better credentials.” I’m not sure why so many people think I, or any other faculty member — at Stanford or elsewhere — would decide to favor one unknown person over another. Sometimes their argument is that they want to work in my area. They seem to fantasize that there is some competition among areas at Stanford, and that I would push for the admission of someone just because they claimed to want to work in an area that I favored. However, it doesn’t work that way at Stanford, or any other American university that I know about.

Admittedly, there are some countries where PhD students are in effect hired by a faculty member and selected by them, but that’s not how it’s done here. At Stanford, a committee examines all applications and picks the ones with the most promise for study in Computer Science. The process is honest and objective. It is impossible to influence it through individual faculty, regardless of whether or not they are on the committee. In fact, I know of some faculty who will count it against you if you send this sort of email.

Whenever I get a “please treat me specially” letter, I respond with the following:

Thank you for your interest in Stanford. All admissions decisions are made by a committee of faculty and graduate students, and there is no point contacting individual faculty in the hope of bringing your case to their attention. Questions regarding admissions should be sent to admissions @ cs.stanford.edu You may also find out more about our department from URL http://www-cs.stanford.edu

Added Nov., 2003: A more recent variation is people asking for “summer internships.” Unfortunately, the same principle applies. You can’t get a student job at a university without being a student at that university. Faculty have a responsibility to serve the needs of the students at the school that pays their salary.

The second sort of email I get a lot of sounds like: “I really like your book on [fill in the blank], and I’m learning a lot. But I just have a doubt about the solution to Exercise 4.5.6. Could you please tell me the answer?” In a slight variant, it’s not a book exercise, but another problem whose solution they would like to see. I’m not that stupid. The chances are 98% that this is a homework assignment, and I’m not going to do your work for you. I therefore have developed a policy of responding to questions about material in my books only to bona-fide instructors. I rarely hear back when these email writers get the following stock response:

Thank you for your note. When I get these sorts of questions, I like to know first what school you are attending, what class you are taking, and who the instructor is (email if possible please). I suggest that first you discuss the problem with your local instructor. If they can't help you, then please ask them to get in touch with me.

Exactly. The doctoral web page for Carnegie Mellon’s doctoral program is http://www.tepper.cmu.edu/phd . All information on applying to the program is available there.