Evolutionary based capacity optimization of a baggage sorting system using a modular cellular automata

Abstract

Baggage sorting systems (BSS) are crucial for running airports beyond a certain passenger capacity. The lack of careful optimization of a given capacity BSS infrastructure leads to an uncomfortable situation for passengers which miss their baggage on connecting flights. In addition there is a security issue if the passenger and its baggage are transported on separated flights. For seasonal assembling of flight plans or long-term infrastructure bottleneck analysis it is of a high importance to know the BSS boundaries for a given demand. Latter replacement of an old BSS by knowing the real flight dependent capacity boundaries, save money investments. However, a little has been done on the optimization of BSS regarding operational issues. In this paper a modular cellular automata is used to optimize the operations issues using an elaborated metaheuristic. An additional case study at Airport Zurich targeting two questions: the gate assignment and the impact of x-ray baggage control throughputs. The computational results show a significant improving of capacity and flexibility in planning the utilization concepts.