Major League Baseball Scheduling

Peter Theis and Jeremy Hastings, MBA students at my home base, the Tepper School of Business at Carnegie Mellon, have independently reminded me that I have been getting some press about the baseball schedule that I should be pointing to. Not all of it has been positive, but most of it talks about how difficult creating satisfying schedules is. For those who don’t know, some colleagues (Doug Bureman, George Nemhauser and Kelly Easton) and I, through our company the Sports Scheduling Group, created the 2005 and 2007 Major League Baseball Schedule. ESPN.com has an article on the 2007 schedule. They talk about some of the rough parts of the schedule:

For baseball players, grousing about the schedule is as routine as chewing sunflower seeds or making rookies wear cocktail dresses and high heels to the airport during the obligatory hazing trip. The average fan might regard it as just another case of millionaires whining, but fans don’t have to step in the box in front of 50,000 people and produce while bleary-eyed and jet-lagged.

Listen closely, and you’ll hear the Pittsburgh Pirates groaning en masse as they look at their schedule and contemplate that geographically challenged Houston-to-San Diego-to-Chicago trip in late September.

Or consider how thrilled the Texas Rangers must be looking forward to a nine-game Detroit-to-Oakland-to-Minnesota jaunt (with no day off) in the final month.

But ESPN.com also talks about the challenges:

Each team has its own unique circumstances. Cincinnati is always home on Opening Day, while Boston plays at Fenway Park each Patriots Day. The Mets have potential traffic and parking concerns when the U.S. Open tennis tournament is in town, and the Minnesota Twins share the Metrodome with the NFL’s Vikings.

And lest we forget, New York, Chicago, Los Angeles, the San Francisco Bay Area and Baltimore-Washington are all two-team markets. In a perfect world, one team will be at home while the other is on the road.

Throw in six pages of whys and wherefores governing scheduling in the collective bargaining agreement, and you have an extremely complicated jigsaw puzzle.

“You can take any short part of a team’s schedule and say, ‘That’s awful. Why would anybody schedule that?'” Feeney said. “But you can’t look at it that way. It’s not a two-week schedule. It’s a 26-week, 30-team schedule.'”

There have also been articles in the San Jose Mercury News and the Seattle Times. The News has the most depressing line (at least to me):

Starting next season, MLB will create the schedule within its offices. In other words, no more outside consultants.

Not happy news for the Sports Scheduling Group!

Sloan-Kettering wins 2007 Edelman Award

The Franz Edelman award is the most prestigious award for the practice of operations research, and each year’s competition is hotly contested. Nominees need to spend significant time preparing their presentations and almost all of them end up involving CEOs or other top executives in the firm.

This year, the winner of the Edelman Award is Sloan-Kettering for work entitled “Operations Research Answers to Cancer Therapeutics.” From the announcement

Yesterday was the first time that the association awarded the Edelman prize for a medical treatment. The Sloan-Kettering win demonstrates how operations research and mathematics are increasingly bringing improvements to health care, not only in the areas of policy, finance, and public health but in diagnosis and treatment, as well.

Dr. Marco Zaider, Attending Physicist in Medical Physics at Memorial Sloan-Kettering Cancer Center received the award together with Professor Eva K. Lee, Director of the Center for Operations Research in Medicine and HealthCare in the School of Industrial and Systems Engineering at Georgia Institute of Technology.

The 2007 Franz Edelman Award winner was announced at a special awards banquet during The Institute for Operations Research and the Management Sciences (INFORMS®) Conference on O.R. Practice in Vancouver. http://meetings.informs.org/Practice07/ The finalists included Coca-Cola Enterprises, Hewlett-Packard, DaimlerChrysler, and the U.S. Coast Guard.

Dr. Lee and Dr. Zaider devised sophisticated optimization modeling and computational techniques to implement an intra-operative 3D treatment planning system for brachytherapy (the placement of radioactive “seeds” inside a tumor) that offers a safer and more reliable treatment.

The real-time intra-operative planning system eliminates pre-operation simulation and post-implant imaging analysis. Based on the range of costs of these procedures, Prof. Lee estimated conservatively that their elimination nationwide could save $450 million a year for prostate cancer care alone.

I am hoping for some press coverage for this (the winning work is very important, as are the contributions of the other finalists), but not much so far (just a couple pickups from health-oriented web sites). Reporters: great opportunity here!

Papers associated with the Edelman finalists will appear in the January-February issue of Interfaces.

Algorithms in the Attic

The February 2007 issue of the Harvard Business Review has an article on “Breakthrough Ideas for 2007” (sorry, pay-only link: HBR isn’t much for making stuff available for free). One of the breakthrough ideas is given by Michael Schrage of the MIT Media Lab under the title “Algorithms in the Attic”, a play on the title Rembrandts in the Attic, a book on unlocking the value of patents (for better or worse). Schrage argues:

For a powerful perspective on future business, take a hard look at mathematics past. As computing gets ever faster and cheaper, yesterday’s abstruse equations are becoming platforms for tomorrow’s breakthroughs. Companies in several industries are now dusting off these formulas and putting them in the service of new products and processes.

Examples Schrage cites are include:

Procter & Gamble has been restructuring its supply chain with complex “expressive bidding” algorithms–based on 1950s linear-programming equations– that allow suppliers to bid online with bundled offerings of products and service levels rather than with standardized lots. Google’s search engine was possible only because the founders adapted a century-old theorem about matrices to software for ranking Web pages according to links from other sites. Networks like the Web can be expressed as matrices, and a relatively simple calculation gives a ranking of how well each site is connected to the rest of the Web. That formula for automatic ranking – which could be understood and appreciated without a PhD – is one of the most lucrative algorithms ever. The math was there for the taking.

Well-known OR researcher Dick Larson gives a nice quote:

“There are huge hidden assets in the operations-research community,” says the MIT professor Richard Larson, a pioneer in probabilistic modeling techniques. “If you gave an army of 20 grad students the mission to rake through the published literature of the past 30
years, they would find stuff that has untapped business potential worth billions
of dollars. There are many clever ideas my students worked on decades
ago that in today’s networked environment would not be an academic exercise
but a real business opportunity.”

Schrage concludes:

Whether looking for breakthroughs or just trying to improve decision making, companies will benefit from greatersophistication around even simple mathematics. A decade ago, big firmsbegan to realize that they were sitting on a treasure trove of underutilized patentsand know-how that could be commercialized for willing buyers. Those “Rembrandts in the attic,” as Kevin G.Rivette and David Kline put it in their 2000 book by that name, needed thekeen eye of an intellectual property curator to appreciate their value. Similarly, we now require quantitative entrepreneurs to seek out existing equations that meet today’s pressingbusiness needs. Technology continues to make that quest faster, easier, and cheaper.

Hmmm…. thinking over my past research doesn’t immediately lead to thoughts of business opportunity, but maybe it is time to pull out those dusty journal articles.

Linda Green on OR in Healthcare

Linda Green of Columbia University was here (Auckland) today and gave a talk on the use of operations research in the health care industry. Most of her presentation was on simple queueing models to gain insight into capacity and scheduling for healthcare. Some of this work has recently been covered in Business Week. One simple “Queueing 101” result that people just don’t understand is that a queueing system with 85% utilization, say, is not 15% inefficient. In fact, this value is the rule of thumb many hospital administrators use to determine optimal intensive care unit (and other hospital unit) sizing. But such a utilization can lead to 10% or more of the patients arriving with no beds for them! The exact number depends on the variability and other statistical measures of the arrival and service processes but aiming for 95% utilization (as some hospitals and districts do) is foolish and dangerous: it will lead inevitably to many turned away (or choosing to leave without being seen, leading to more critical later issues). The world would be a much better place if more people understood some of the basic insights that OR provides.

Optimizing Airline routes

Thanks to Chad, a Tepper MBA student, who pointed out the the Wall Street Journal of March 6, 2007 has an article on optimizing international airline routes. It turns out that countries have complicated costs for airplanes flying in their space, and rerouting the planes can lead to pretty significant savings (on the order of $1,400/flight, which multiplies out to millions per year). From the article:

The formulas countries use to compute their overflight fees vary widely. Cameroon, in Africa, bases its charges on the maximum takeoff weight, with an international flight passing over the country paying from €102 to €204 ($134 to $267). Canada assesses 3.6 Canadian cents (3 U.S. cents) times the distance flown times the weight of the aircraft, plus C$97 per flight for air-traffic control coverage over the North Atlantic. United Kingdom overfly rates are three times as high as Ireland’s rates, and German rates are at least twice as high as Canada’s, according to international aviation specialists.
The U.S. funds its air-traffic-control system differently. Instead of flyover fees, passengers pay multiple taxes to the airlines, which pass the money on to a trust fund. On domestic flights fliers pay 7.5% of the cost of the ticket, plus $3.40 for each flight segment. Passengers on international flights pay $15.10 in fees for coming into and leaving the U.S. Minimizing overflight fees must be balanced against additional fuel costs if an alternative route is less direct. The software systems track a slew of additional data: weather; airport locations and runways; weight and performance of each airplane in the carrier’s fleet; temporarily blocked airspace and the locations of fixed air routes, which change daily due to winds.
The computers churn through multiple scenarios, including minimum time, minimum fuel and minimum cost, and determine which is the best solution for the maximum payload, given up-tothe-minute wind and weather information.

It is surprising the savings possible:

British Airways in 2003 finished installing such software on its route network, replacing a homemade system that one pilot describes as “a blunt instrument.” As a result, it has drastically changed the routing of its Sao Paulo-London flight. Instead of flying in a straight line and crossing over Portugal, Spain and France before entering U.K. airspace, the airline now takes a northerly track over the Atlantic and enters the U.K. over Cornwall. Capt. Tim de la Fosse, BA’s general manager of flight technical, says the new path saves £3,000 ($5,767) per one-way flight in European overfly fees, uses one fewer ton of fuel and is 18 minutes shorter in duration.

OR and Air Security

Operations research has been getting a lot of press recently due to a study about the effectiveness of “no-fly” lists in preventing terrorism. Long-time researcher of airline safety, Arnie Barnett along with Harvey Mudd professor Susan Martonosi found, using OR models of course, that it is best to screen all passengers, rather than try to pre-screen so-called safe passengers. Here are some excerpts from the LA Times:

Operations research is a little-known but valuable tool for such things as scheduling airline flight crews, planning National Football League seasons and even designing waiting lines at Walt Disney World. And in a report released on Monday, it was used to assess the effectiveness of the nation’s security screening of airline passengers.

Using a mathematical model, Susan E. Martonosi, an assistant professor of mathematics at Harvey Mudd College in Claremont, and Arnold Barnett, a professor of management science at MIT, sought to explore the effectiveness of the “no-fly” lists in preventing terrorism. The conclusions they reached were less remarkable perhaps than the way they evaluated the program.

They found that improving the screening required of all passengers at security checkpoints would do more to enhance security than further refinements to the pre-screening of passengers by no-fly lists.

Here is a presentation on the topic.  Check out your December issue of Interfaces for the full paper, along with a number of other papers on homeland security.

President Clinton, AIDS and Operations Research

Clinton FoundationIt is heartening to see former President Clinton talk about “Operations Research” and even better to see outside groups see the promise of our field. At an address at the 16th Annual International AIDS Conference, President Clinton announced a new Consortium for Strategic HIV Operations Research. From the transcript (page 13/14):

Second point I want to make is while more money is necessary, it is nowhere near sufficient. It is our moral obligation to ensure that the enormous contributions already made and those that will be made are used most efficiently. Every single wasted dollar puts a life at risk.
A few days ago, my foundation unveiled our consortium for strategic operation research here in Toronto. It’s an initiative designed to help ensure that this huge investment of resources results in the highest quality care, most efficiently delivered for as many HIV infected people as possible. We want to apply the same planning methods that Fortune 500 companies use to manage their operations, so that we can make the most effective use of what will always be scarce resources until the number of people who are HIV positive begins to drop dramatically. Using simple open-source computer models, we’ll be able to help governments save more lives with the same human and financial resources.

Wow! An obvious reference to operations research and open source in the same paragraph!

A few months ago, I talked to some researchers at the Clinton Foundation. Often “Operations Research” in AIDS/HIV research is what we would call “Statistical Experimental Design”: how to best measure the effect of certain treatments. For instance, there is a book available online entitled: “Designing HIV/AIDS Intervention Studies: An Operations Research Handbook” that will not be recognizable as operations research as our field defines it.

While important, this approach ignores 99% of operations research. Issues like optimal resource allocation, stochastic models of disease spread, simulation and so on are equally or more important, but are under-studied in this area.The Clinton Foundation people seem to understand this, and want to bring the full power of OR to this field. The CSHOR has in place a simulation model of clinics that can be modified to fit local costs/resource availability to determine, for instance, the effect of having another nurse. The Q&A directly addresses the role of OR:

Why was CSHOR created?

The emerging field of operations research offers a practical and strategic approach to future planning for developing countries. Operations research can be performed on the ground, in real-time, to guide decision making at a single clinic or a regional or national HIV treatment program. Local data and best practices from programs around the world can be combined to help ensure consistency and quality of care.

Operations research is increasingly critical; as ever-vaster resources are poured into national HIV treatment programs, it is crucial to be sure they are used as efficiently to provide high-quality treatment and care for as many people as possible.

CSHOR was launched in response to direct appeals from CHAI’s partner countries for assistance with resource planning and allocation.

I am not sure “emerging field” is appropriate for a 60 year old field, but the rest is very encouraging.

OR has a huge amount to offer this area, and I am absolutely thrilled that the Clinton Foundation is using the skills of our field

More on Air Taxis

My friend and business partner (in sports scheduling), George Nemhauser, read my post on air taxis and wrote to remind me that Georgia Tech worked with DayJet on the optimization issues that are key to the efficient running of their operation. This led me to an USA Today article by Kevin Maney that I had missed on the subject. The article covers the optimization issues very well:

Tech industry veteran Ed Iacobucci seems an improbable guy to start a new kind of airline. It’s like Donald Trump starting a chain of Laundromats, or Tom Cruise marketing an anti-depression drug.

Pretty jarring, in other words.

But he isn’t really starting an airline, much as eBay didn’t start a flea market. Iacobucci is a one-time IBM tech whiz and founder of software maker Citrix Systems. Over the past four years, he and his team have built a breakthrough computer system for solving highly complex optimization problems.

An optimization problem is like when a mom has to pick up one kid at soccer, one at dance, buy groceries, walk the dog and volunteer at church, and has to figure out the most efficient way to do them all. Now try that for hundreds of moms and hundreds of tasks all at once.

“This is hard stuff,” Iacobucci says. “There’s a lot of new science involved.”

His team is using this system to launch DayJet, the first true on-demand air service. Such a service could not exist without the new computer system. Basically, Iacobucci has started a technology company that will make its money by flying people around.

I love the phrase “a technology company that will make its money by flying people around”. I would like the phrase “an operations research company that will make its money by flying people around” even better, because that is what DayJet really is. Just like Amazon is an operations research company that makes its money by selling books and more, and FedEx is an operations research company …

The article goes on and makes a very clear point about the scale of the optimization, and the need for timely schedules:

If you have a bunch of little jets and a bunch of people in different cities who want a ride, Iacobucci thought, software should be able to figure out the most efficient way to scatter the planes so they can transport the people — while charging enough to make a profit but not nearly as much as a traditional charter plane service.

Good idea, until you start considering all the variables involved. Matching people, cities and aircraft seats is tough enough, but add in crew schedules, maintenance, fuel costs and the uncertainties of weather — plus the need to quote ticket prices before all the variables are in place — and you’ve got a computational mountain no one had yet climbed.

“When I told our team what we wanted to do, they went like this,” Iacobucci says as he makes a cross with his fingers — the way you’d ward off vampires. That’s serious, considering his team includes a couple of former Soviet rocket scientists and the complexity theory department at Georgia Tech, which helped DayJet crack the problem.

As customers put in their requests, the system continually crunches all the departure and arrival requests, plane availability, weather patterns and so on, coming up with a new best answer for schedules and prices every five seconds, always trying — as the DayJet folks say — to get the solution “within 2% of optimality.”

You have to appreciate how remarkable that is. When you’re making everyday, multi-faceted decisions — What should I make for dinner? Should I finish this report or see my kid’s soccer game? — it’s pretty unlikely you ever get within 2% of optimality. I think Donna Reed used to, but I’m sure that’s escaped every other human since.

The DayJet system crunches answers and ranges of probability until a couple of hours before jets would have to take off. “Then the schedule starts to gelatinize,” says Brad Noe, DayJet’s VP of engineering. “And it comes up with a plan.”

This is a great example of academia/business interaction in operations research to come up with businesses that could not exist twenty years ago.

UPS, OR, and US News and World Report

US News and World ReportUS News and World Report has an article in their July 31 issue on how UPS uses technology to better handle packages. In the hypercompetitive world of package delivery, the need to use OR to create efficiencies is very strong.

Perhaps no industry has more effectively embraced the power of digital technology to modernize operations–even more so than airlines, which were long seen as leaders in cutting costs and boosting revenues through computers. “The delivery companies have leapfrogged ahead,” says Satish Jindel of SJ Consulting Group.

In their tight competition, industry leaders UPS and FedEx have one-upped each other for years in rolling out hand-held computers, wireless links, and new uses of mainframe computing power. Now UPS is pushing automation to the last mile of its delivery network, down to charting the order in which packages are loaded on a truck and the most efficient route for delivering them. Dubbed “package flow technology,” the latest upgrade is costing $600 million and taking three or four years to implement across the company’s 70,000 routes. When the upgrade is in place, UPS says it should get back that $600 million every year in saved costs, as more-efficient routes cut 100 million miles of driving time and 14 million gallons of gas. “It’s fundamental–a major, major change that will even change the way our drivers run their routes,” says Chief Information Officer David Barnes.

They even found room for a quote from me:

Pushing automation to the fringes of its operations is only possible because of the mass of data that UPS computers have been collecting as parcels move through its central hubs, and thanks to advances in math and computing power. Delivery companies have become leaders in “operations research,” a growing field that uses mathematical models to streamline processes, says Michael Trick of Carnegie Mellon University. “It used to be that only airlines could worry about issues like routing,” he says.

Hmm… did I really say the last part? Well, the point I was trying to make was that while airlines where at the forefront of practical OR, we are now seeing it in lots more places. UPS is a good example, though they are catching up with firms that caught the OR bug early, like FedEx:

Bart Haberstroh, who delivers for UPS in St. Charles, Mo., a St. Louis suburb, remembers when “the joke was that the sharpest tech UPS had was a sharp pencil,” he says as he wheels his brown van through familiar streets.

With the amount of OR pouring into their systems, that is no longer the case.

More OR in the New York Times

There is more OR in the New York Times, not that they would mention our field by name. There is an article today about new air-taxi services. There are a number of new airplanes in the lightweight group (under 10,000 pounds) able to carry 4 passengers or so. This is leading a number of companies to start serious air-taxi services:

Enter the air taxi, an idea whose time has come. At least that is the hope of the entrepreneurs placing big bets on a new niche they plan to create in aviation. Their idea is to offer faster, more convenient air travel at a price that falls somewhere between private jets and commercial airlines.

For years, questions about the size of an air taxi market have been largely theoretical. But that will change this year, as Eclipse Aviation of Albuquerque begins building the Eclipse 500, a six-seat plane. The company expects the plane will receive its long-awaited certification from the Federal Aviation Administration as soon as this week.

With the Eclipse, two start-up airlines, Linear Air and DayJet, say they can ferry business travelers to hard-to-reach outposts with fewer frustrations — and get them home in time for dinner with their families.

Economically, these jets cost somewhere between commercial prices and charter prices:

Air taxi operators say they can offer customers seats ranging from $1 to $3 a mile, compared with $9 to $13 a mile on charter jets, or up to $15 a mile on slightly larger private jets. Regional commercial airlines like SkyWest, by contrast, average less than 16 cents a mile flying 50-seat planes, but as much as five times that on less-traveled routes where air taxis plan to compete, industry executives say.

Of course, key to efficiency is (what else?) operations research:

Making Mr. Iacobucci’s flying limo work will require substantial computing power to analyze routes and passengers’ schedules almost instantly. That does not deter Mr. Iacobucci, who spent his career in the software industry, first at I.B.M. and later at Microsoft. He spent $20 million and four years developing DayJet’s reservation system. DayJet has already ordered 239 Eclipse 500’s, making it Eclipse Aviation’s biggest customer.

I love the way newspapers use a word like “analyze” when the reality is that signficant modeling and optimization must be done to handle systems such as this.