Abstract
This research details control factors of baggage handling system (BHS) with carousel-based unloading zone, and simulation optimization is used to find the best buffer zone mechanism setting of BHS for reducing congestion in the system. Taiwan Taoyuan International Airport Terminal Two (TPE) is taken as case study. With the growing number of tourists recently, insufficient capacity of BHS has been a problem faced by TPE. Reducing the number of manual handling baggage and congestion in the system is an important issue. The buffer zone mechanism settings in different area and time-period are presented. The baggage arrival in peak-time is not the same as it in non-peak-time, so is it in the different area of the system. The important control factors of BHS are buffer zone mechanisms including time bucket of the each buffer zone and the number of main buffers opened which decreases manual handling baggage, but increases reflux baggage. Manual handling baggage make ground crews sort the baggage with multiple flights which is more labor intensive, and has higher error rates; Much reflux baggage may affect the process of baggage from check-in counter, and make passenger wait. Therefore, the study is to minimize the consolidation goal with the number of manual handling baggage and reflux baggage. In this research, considering different buffer zone mechanism settings in different area and time-period, the results are superior to that of current control factor setting of BHS in reducing the number of manual handling baggage, 15% on average. Based on the stochastic baggage arrival, optimal computing budget allocation is used for saving five days of simulation time compared with equal resource allocation. By comparing OSAS with OCBA, there is even five hours saving of the simulation time. The study found the best alternative of buffer zone mechanism settings to minimize the number of manual handling baggage and reflux baggage. Furthermore, the traveling time should meet the airport requirement, and the simulation is used to validate the performance measure. At last, the result meets the requirement as well as evaluating the feasibility of the decisions.