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."
I've been looking for a more sophisticated follow-up to SimTower for a while now. I'd buy Otis Elevator Tycoon.
10 PRINT CHR$(205.5+RND(1)); : GOTO 10
I expect the job has its ups and downs just like any other.
Was a mathematician really needed for this job:
During the recent $550 million upgrade of the Empire State Building, Ms. Christy was asked whether she could help get more people up to the observation deck. She said she couldn't get more people into a car but could move them up more quickly. So she increased the elevators' speed by 20%, to 20 feet per second. Now the cars can rise 80 floors in about 48 seconds, 10 seconds faster than before.
Isn't making the elevator go faster a job for an engineer? Does one really need to be a mathematician to know that a faster elevator moves people faster?
News flash: State machines don't crash.
Each elevator has its own controller, which is relatively simple. When there's more than one elevator, there's also a group controller, which makes the decisions about which elevator responds to which call. All the smarts are in the group controller.
Many elevators have a key switch for "independent service", which disconnects them from the group controller. Then they only respond to the buttons in the car. The group controller isn't necessary to basic elevator operation.
... when elevators can move in more than one plane: 10 PRINT CHR$ (205.5 + RND (1)); : GOTO 10
It must have been something you assimilated. . . .
That's an undergraduate level general optimization problem.
The one in TFA is a graduate level optimization under a particular set of data constraints. So the generally optimal algorithm for elevators has to a assume a random distribution of people to be picked up and destination floors (head is in a random location wants data from some other random location) - but in practice you may be need sequential access or the like. With elevators, I would expect that in mornings in residential buildings people want to empty out so the 'resting' point would to close to 2/3rds or 3/4ths of the way up, but in the evenings it would be the reverse direction, and business would be the reverse of residential. Schools have a somewhat more random use of bursty every hour up and down, and really big businesses may want dedicated elevators between floors shared by particular companies because there's a lot of daily movement within the floors of a company but not so much outside their area.
Lunch of course adds another complication.
There's a lot of neat work into simulating the data for a building that doesn't exist yet, or measuring the data for a building that exists but has a bad algorithm. And then trying to tailor your elevator to the specific behaviours that actually exist.
Does it also simulate who farted?
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