| 摘要: | 隨著廉價航空的興起及紅眼班機的增加，桃園國際機場基於日益增加之旅客量，為了因應龐大的運輸量，故於2015年第二航廈將出境部分原先的南北座直線型行李卸載道全面更新成轉盤型行李卸載轉盤，以提升地勤人員作業之效益。在實務上，目前桃園國際機場之出境行李卸載轉盤操作上，當行李卸載轉盤遭遇臨時性故障時，機場仍以人工方式進行調度，未以系統最佳化方法，調整其航班與卸載轉盤的指派，不僅難以在短時間內有效地調整其航班與行李卸載轉盤的指派，更缺乏效率及效果，進而造成資源浪費與成本增加。因此，如何於短時間內同時考慮營運者及使用者（乘客、航空公司等）成本或服務水準，有效地調整航班與行李卸載轉盤指派，使系統擾動狀態能儘速地恢復至正常營運，實乃當前重要之課題。本研究針對機場旅客行李卸載轉盤發生臨時性故障之問題，以最小化所有指派航班之擾動時間加上航班作業重疊時間為目標，構建機場航班與行李卸載轉盤即時指派之模式。由於預期實務問題的規模甚大，勢難以利用現有最佳化軟體求最佳解，故本研究擬利用基因演算法發展一啟發式解法以有效地求解模式。為測試模式之實用性，本研究擬以國內某國際機場之現有機場行李卸載轉盤設施及營運為例，進行範例測試，並針對不同參數進行敏感度或方案分析。本研究期望所發展的模式及求解方法除能提供學術界參考之外，更能提供機場管理單位，在面臨行李卸載轉盤發生臨時性故障時，有效地調整航班與行李卸載轉盤之指派，幫助機場管理單位提升行李卸載轉盤之使用效率，以減少地勤人員之不便性，進而維持機場的服務水準。 ;With the rise of budget airlines and the increase of red-eye flights, to cope with the huge passenger volume the straight-line baggage conveyor in the departure section in Taoyuan International Airport had been changed to baggage unloading carousel in 2015, hoping to improve the efficiency. In practice, for the current operation of Taoyuan international airport departure baggage unloading carousel, when there are some baggage unloading carousels temporarily broken down, the airport authorities still adjust the assignment of flights to baggage unloading carousels in a manual way without a system optimization analysis, which is neither effective nor efficient, usually resulting in waste of resources and increase of costs. Therefore, it is currently an important issue to effectively adjust the assignments of flights to baggage unloading carousels in a short time, considering the cost of the operator and the level of service of users (passenger, airline, etc.), so that the system can be quickly restored to its normal operation.Aiming to minimize the total of disturbance time and overlapping time of all flights, this study will construct an assignment model of flights to airport baggage unloading carousels, for the temporary malfunction of airport passenger baggage unloading carousels. Because the problem sizes faced in real practices are expected to be very large, it would be difficult to use the CPLEX to solve for the optimal solution. Therefore, this research will adopt the genetic algorithm to develop a heuristic method that can efficiently solve the model. Finally, a case study, coupled with a number of sensitivity/scenario analyses, will be performed using real data from an international airport in Taiwan to evaluate the proposed model and heuristic algorithm. Finally, beside the contribution to the academics, we hope that the model and the solution algorithm could be useful references for the airport authorities to optimize the adjustment of flights assigned to baggage unloading carousels for the temporary malfunction of airport passenger baggage unloading carousels, so as to improve the usage of passenger baggage unloading carousels, reduce the inconvenience of ground crews, and maintain the airport level of service. |
