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Bike shares can be perfect!: Solving the commuting algorithm

The mathematician and the mayor have little in common, but each would like to bridge the gap. Mayors are absorbed by the idea that data can anticipate traffic jams and crowded trains. Mathematicians are enticed by the challenge of the city. Just as the Fibonacci sequence arises in flower petals and the Golden Ratio structures the nautilus shell, so fractals can model suburban development patterns and power laws predict a city's infrastructure-to-population ratio.

Bike share systems provide a particularly appealing meeting point. For researchers working from travel data, a bike share system is a unique record of how people move in the city. For mathematicians, bike share is a riddle with real-world implications. Between data mining and mathematical models, analysts hope the complexities of designing and managing a bike share system can be reduced to numbers and algorithms, or even solved.

This week, Dream City looks at the unruly mix of math, experience and politics that goes into the management of a bike share system. In a second column next Saturday, I'll turn to the data that emerges from the system, and the secrets it may hold for the city.

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