Via Nautilus:
modeling the real world, with constraints like melting ice cream and idiosyncratic human behavior, is often where the real challenge lies. As mathematicians, operations research specialists, and corporate executives set out to mathematize and optimize the transportation networks that interconnect our modern world, they are re-discovering some of our most human quirks and capabilities. They are finding that their job is as much to discover the world, as it is to change it.
Unhappy Truckers and Other Algorithmic Problems - Issue 3: In Transit – Nautilus
Points:
- “…an ongoing question—the question—in computer science: whether or not P equals NP. As summarized with blunt elegance by MIT’s news office, “roughly speaking, P is a set of relatively easy problems, NP is a set of incredibly hard problems, and if they’re equal, then a large number of computer science problems that seem to be incredibly hard are actually relatively easy.” The Clay Mathematics Institute offers a $1 million reward to a meta-problem hovering like a mothership over the Car 54 challenge and its ilk: proving that P does or does not equal NP.”
- “Until the early 1980s, UPS drivers used to have one simple goal: to get all the packages in their truck delivered by the end of the day.”
- “But then, in 1982, the world changed: Next-day air delivery was introduced. Suddenly, there were an increasing variety of time “commits;” packages had to be at one address by 10:30 a.m., another by 1:30 p.m., another by noon. There were new time constraints for package pickups as well. It was no longer just an optimal routing problem, but an optimal scheduling problem. And the one thing UPS suspected was that it was not doing things optimally.”
