Geun-Sik Jo and Kang-Hee Lee, Inha University; Hwi-Yoon Lee and Sang-Ho Hyun, Korean Air
In this project, we have developed the Ramp Activity Coordination Expert System (RACES) in order to solve aircraft parking problems. RACES includes a knowledge-based scheduling system which assigns all daily arriving and departing flights to the gates and remote spots with domain specific knowledge and heuristics acquired from human experts. RACES processes complex scheduling problems such as dynamic inter-relations among the characteristics of remote spots/gates and aircraft with various other constraints, for example, customs and ground handling factors at an airport. By user-driven modeling for end users and near optimal knowledge-driven scheduling acquired from human experts, RACES can produce parking schedules for about 400 daily flights in approximately 20 seconds, whereas it normally takes human experts 4 to 5 hours to do the same. Scheduling results in the form of Gantt charts produced by RACES are also accepted by the domain experts. RACES is also designed to deal with the partial adjustment of the schedule when unexpected events occur. After daily scheduling is completed, the messages for aircraft changes and delay messages are reflected and updated into the schedule according to the knowledge of the domain experts. By analyzing the knowledge model of the domain expert, the reactive scheduling steps are effectively represented as the rules, and the scenarios of the Graphic User Interfaces (GUI) are designed. Since the modification of the aircraft dispositions, such as aircraft changes and cancellations of flights, are reflected in the current schedule, the modification should be sent to RACES from the mainframe for the reactive scheduling. The adjustments of the schedule are made semi-automatically by RACES since there are many irregularities in dealing with the partial rescheduling.