One Cool Day Job: Building Algorithms For Elevators

McGruber writes "The Wall Street Journal has an article about Theresa Christy, a mathematician who develops algorithms for Otis Elevator Company, the world's largest manufacturer and maintainer of people-moving products including elevators, escalators and moving walkways. As an Otis research fellow, Ms. Christy writes strings of code that allow elevators to do essentially the greatest good for the most people — including the building's owner, who has to allocate considerable space for the concrete shafts that house the cars. Her work often involves watching computer simulation programs that replay elevator decision-making. 'I feel like I get paid to play videogames. I watch the simulation, and I see what happens, and I try to improve the score I am getting,' she says."

Comments

maybe they should release it as a game

[Trepidity]

'I feel like I get paid to play videogames. I watch the simulation, and I see what happens, and I try to improve the score I am getting,' she says.

I've been looking for a more sophisticated follow-up to SimTower for a while now. I'd buy Otis Elevator Tycoon.

Re:maybe they should release it as a game

[the_rajah]

I designed the hardware and wrote the code for a much smaller elevator company for 25 years... All written in assembly language running on an 8085 CPU with 256 bytes (Yes, bytes) if RAM and 8K bytes of EPROM. It doesn't take much to handle the basics when you're using assembly language. I've done up to 26 stops in a multi-car group with that setup. Each elevator is independent and can run on its own, but they communicate with each other to handle dispatching so multiple cars coordinate their activity.

Optimizing is worthwhile, but adds a lot of complexity. You have to take into account for car locations, direction, speed, where car and hall calls are locatedand have to figure in such things as door times to calculate which car can service a hall call soonest.

As the author says, it's a set of interesting problems and I've had fun with it. Yes, the equipment I designed and wrote the software for is obsolete now, but there's a lot of it out there so I'm anticipating writing updates for a while longer as I head toward eventual retirement.

Sounds good but . . .

[Anonymous Coward]

I expect the job has its ups and downs just like any other.

Re:Sounds good but . . .

[Hognoxious]

Careful, I hear it's easy to get shafted.

Re:Mathematician?

[Samantha Wright]

A professor once described to me an elevator system at his former place of employment that used machine learning to try and anticipate where the elevator should be when not in use. At the start of the day, for example, the elevators should rest on the ground floor, so that they can collect people going up; similarly, toward the end of the day, they should rest at the top, since the overwhelming majority of people would be going down.

In a real-world setting you may have other phenomena that actually need to be learned, such as different groups taking lunches at set times of day, large meetings that cause several floors to congregate on one, et cetera. This problem can be considered from several different angles within ML; either as a regression problem or classification, for example.

Speed also needs to be optimized not just based upon the desire to reach the destination quickly, but also considering the rate at which the mechanisms will wear out, the energy consumption caused by more rapid movement, and to encourage people to use the stairs.

Given the potential complexity of how many parameters and models can potentially be considered... yeah, you want someone with a serious background in applied optimization, statistics, or artificial intelligence.