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The Elevator Optimization Problem.
Recently, I completed a small project that required me to make suggestions for optimizing an elevator configuration within a theoretical high-rise in New York City. The building is set up as follows. Entrants to the building must first swipe badges through a security system, then they can push the elevator call button and wait for an elevator to arrive. I was asked to answer 5 main questions, and to only spend a couple of hours completing the task. The main questions were:
Provide an overview of the current state of elevator wait times.
Figure out the overall average wait time.
Determine the times during the day where the wait times are longer.
Determine the floors where the elevator wait times are longer.
Provide a minimum of 2 recommendations on how to optimize the elevators’ configuration to reduce wait times.
In order to answer these questions, 2 datasets were provided. One called people.csv which documented all of the swipes into the buildings security system, and another called simulation.csv which was a log of each elevator’s status and operations over the course of the few months which we had data. There were a total of 4 elevators in the 20 story building.
