PT Journal
AU Wuddi, P
   Fottner, J
TI Self-Learning Problem Prioritization for Operating Tugger Train Systems
SO Logistics Journal : Proceedings
PY 2021
VL 2021
IS 17
DI 10.2195/lj_Proc_wuddi_en_202112_01
DE Leitsysteme; Logistiksteuerung; control systems; decision-making; logistics control; operational control; operative Steuerung; selbstlernende Systeme; self-learning systems
AB For the operational control of logistics systems, the application of optimization methods using self-learning algorithms is increasingly the subject of research and development. Knowledge management systems, which address the specific reaction to deviations, i. e. disturbances and fluctuations of system parameters, form a special application use case. This paper discusses in detail, how such a system can evaluate, which present deviation in the logistic system should ideally be subject to the reaction of the control system. Several ideas are part of the discussion and narrow down to four different approaches. An overall evaluation and a synthesis of the individual approaches to a universally valid and applicable approach follow. Furthermore, future possibilities for enhancement complete the paper
ER