Multi-Objective Optimization of Airport Baggage Transport Vehicles' Scheduling Based on Improved Genetic Algorithm Southeast University, School of Transportation

Format:

Book

Conference/Event

Author/Creator:

Jiang, Han, author.

Contributor:

Qian, Pinzheng

Zhang, Haiyan

Zhang, Jian

Conference Name:

SAE 2023 Intelligent Urban Air Mobility Symposium (2023-10-20 : Hangzhou, China)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2023

Summary:

Transporting baggage is critical in airport ground support services to ensure smooth flight operations. However, the scheduling of baggage transport vehicles faces challenges related to low efficiency and high costs. A multi-objective optimization vehicle scheduling model is proposed to address these issues, considering time and space costs, vehicle utilization, and passenger waiting time. An improved genetic algorithm (IGA) based on the large-scale neighborhood search algorithm is proposed to solve this model. The simulation experiment is conducted using actual flight data from an international airport. The IGA algorithm is compared with the standard genetic algorithm (SGA) based on experimental results, revealing that the former achieves convergence in a significantly shorter time. Moreover, the scheduling paths of baggage cars that violate flight service time window requirements are significantly lower in the final scheduling scheme under the IGA algorithm than in SGA. Additionally, there is a 14.89% reduction in total scheduling costs compared to SGA. The results indicate that the proposed model and algorithm are feasible and effective, which can provide a reference for the actual operation of the airport

Notes:

Vendor supplied data

Publisher Number:

2023-01-7090

Access Restriction:

Restricted for use by site license