Elevator group control using distributed genetic algorithm

TL;DR: This work has studied the applicability of genetic algorithms to the optimization of elevator group control parameters to minimize the average passenger waiting time in a simulated office building.

Abstract: In this work we have studied the applicability of genetic algorithms to the optimization of elevator group control parameters. The goal was to minimize the average passenger waiting time in a simulated office building. The elevator group control consists of a set of elevators and controllers. At the highest level of the system hierarchy the elevator group controller decides which elevator serves which call. The decision is based on the actual calls, state of the elevators (location, direction, load) and on the estimation of the traffic situation like: incoming, interfloor, outgoing, which gives some idea how the calls will be distributed within a few minutes time period. Especially in office buildings the traffic type depends on the time of the day. This allocation problem, which seems to be quite simple, turns out to be a very difficult control problem in practise and is one of the features how elevator companies can competed with one another.