[jpren]

As several others have suggested, the elevator should behave differently at different times throughout day.

A smart elevator algorithm would adapt to the arrival behavior of people in a building through some clever stochastic simulation and modeling. For example, a simple model that could work quite well is to optimize for (read: minimize) the average time any passenger would wait for an elevator to arrive. But to do this, we need to model how frequently people request an elevator on each floor over the course of the day.

Modeling elevator requests - We can assume that the number of people who request the elevator on each floor is a Poisson process with a mean of n. On a representative day (i.e. for an office building, choose a weekday), we can observe the number of people who arrive at the elevator each hour. This data would drop in as the n in our Poisson arrival processes.

Computing optimal solutions - Using a statistical library, we can start generating simulated arrival data and apply integer optimization algorithms to determine which floor the elevator should rest on when there are no elevator requests, for each hour of the day.