Detalle Publicación

Improving waiting time and energy consumption performance of a bi-objective genetic algorithm embedded in an elevator group control system through passenger flow estimation

Autores: Beamurgia Bengoa, M. (Autor de correspondencia); Basagoiti, R.; Rodríguez Carreño, Ignacio; Rodríguez Chacón, Victoria María
Título de la revista: SOFT COMPUTING
ISSN: 1432-7643
Volumen: 26
Número: 24
Páginas: 13673 - 13692
Fecha de publicación: 2022
Passenger waiting time is a significant issue related to the quality of service of a multiple lift system; however, energy consumption reduction is also an important concern in the lift industry. In this paper, we evaluate different versions of a genetic algorithm (GA) published previously by the authors with several relevant adjustments for the lift dispatching problem to minimize passenger waiting time and/or energy consumption. To the raw GA with adjustments (that works under the assumption one call-one passenger), we incorporated several elements: a passenger-counting module using origin-destination matrices, and the activation of certain policies (zoning and/or parking) under different detected traffic profiles (up-peak, interfloor or down-peak profiles). Besides, we added a proportional integral controller (PI) to assign different weights to passenger waiting time and energy consumption to evaluate the performance of our GA. Different versions of this GA, minimizing passenger waiting time and/or energy consumption, were compared among them and to a conventional control algorithm using three different types of simulated profiles: a mixed one, three well-known full day office profiles and three different step profiles. The results showed that the bi-objective GA version with the estimation of the number of passengers behind a call, i.e. the passenger forecasting, together with the parking policy for up-peak or down-peak conditions significant