Elevator Group Supervisory Control System Using Genetic Network Programming with Functional Localization

Abstract

Genetic Network Programming (GNP) having a directed graph structure has been proposed as a new method of evolutionary computation. Recently, GNP has been applied to elevator group supervisory control system (EGSCS), a real-world problem, to demonstrate its applicability and effectiveness. Its previous study considers the known and fixed traffic flow, however, it is changed dynamically with time in real elevator systems. Therefore, an EGSCS with dynamic adaptive control considering such changes should be studied for practical applications. In this paper, we have applied GNP with functional localization to an EGSCS to construct such an adaptive system. In our proposal, the switching GNP can switch the functionally localized GNPs (assigning GNPs) based on the special traffic. Simulation confirmed the adaptability and effectiveness of our proposal in daily officebuilding traffic.