Goto

Collaborating Authors

 Tsang, Francis Ming Fai


Stand-Allocation System (SAS): A Constraint-Based System Developed with Software Components

AI Magazine

The stand-allocation system (SAS) is an AI application developed for the Hong Kong International Airport (HKIA) at Chek Lap Kok. The system ensures a high standard of quality in customer service, airport safety, and use of stand resources. This article describes our experience in developing an AI system using standard off-the-shelf software components. SAS is an example of how development methodologies used to construct modern AI applications have become fully inline with mainstream practices.


Stand-Allocation System (SAS): A Constraint-Based System Developed with Software Components

AI Magazine

In addition, to cope with conflicts caused by changes in actual operations, the airport authority also needs to make real-time problem-solving decisions on stand reassignments. the Hong Kong International Airport The stand-allocation system ( Figure world's busiest international airports in terms 1 is a snapshot of the The Although there were some initial hitches when system is installed and used in the Airport the new airport opened on 6 July 1998, operations Control Center (ACC), which is located in the quickly returned to normal within a control tower. Within a month, operational statistics management, and reactive scheduling capabilities surpassed those of the old airport--80 for stand management. The system supports percent of all flights were on time or within 15 concurrent use by multiple operators in minutes of schedule, all passengers cleared nonstop 24-hour-a-day operations because immigration within 15 minutes, and average HKIA is a 24-hour airport. Typically, a human operator must have several years of experience to acquire enough knowledge about airport operations before he/she can produce a "good" quality stand-assignment plan. Generating an allocation plan manually not only requires a highly experienced individual but is also very time consuming because it requires balancing many objectives against many possible alternatives.