Simulation Optimization of Airport Baggage Import System Based on Multi-objective Wolf Pack Algorithm

Authors

Yifei Tao, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650504, ChinaFollow
Xiaopeng Ding, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650504, ChinaFollow
Junbin Luo, Kunming Logan-KSEC Airport System Company Ltd, Kunming 650236, China
Xiao Fu, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650504, China
Jiaxing Wu, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650504, China
Yirong Li, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650504, China

Abstract

Abstract: Aiming at the problems of long waiting time for passenger baggage import and high system energy consumption during the operation of the baggage import system in civil aviation airports, a simulation optimization framework for solving this problem is proposed by comprehensively considering the influence of key control parameters on the operation efficiency of the baggage import system in airports, including the virtual window control mode, the operation speed of the collection belt conveyor, the length of the virtual window and the number of check-in counters opened at the same time. By analyzing the actual operating conditions of the airport baggage import system, a parametric simulation optimization model is established. To minimize the average waiting time for passenger baggage import and system energy consumption, combined with the actual constraints in the process of system design and operation, a mathematical model of the problem is established, and a multi-objective adaptive parallel wolf pack algorithm is designed to solve it. Aiming at the characteristics of the proposed problem and the shortcomings of the classical wolf pack algorithm, such as easy falling into the local optimum and slowing convergence speed, the algorithm proposes a single chain coding method of mixed integer and real numbers, which combines the opposition-based learning strategy to generate the initial population, introduces the adaptive walk probability mechanism and the parallel mechanism of intelligent behavior, adopts the local and global adaptive neighborhood search and heuristic optimization strategy to realize the intelligent behavior search of the wolf pack algorithm, and employs Pareto non-dominated sorting method for optimization iteration and obtains the optimal solution set. Taking the baggage import system of a large international aviation hub airport in China as an example, the comparative experiments of different scales and algorithms are designed to verify the effectiveness and superiority of the method proposed.

Recommended Citation

Tao, Yifei; Ding, Xiaopeng; Luo, Junbin; Fu, Xiao; Wu, Jiaxing; and Li, Yirong (2024) "Simulation Optimization of Airport Baggage Import System Based on Multi-objective Wolf Pack Algorithm," Journal of System Simulation: Vol. 36: Iss. 7, Article 13.
DOI: 10.16182/j.issn1004731x.joss.23-0437
Available at: https://dc-china-simulation.researchcommons.org/journal/vol36/iss7/13

First Page

1655

Last Page

1669

CLC

TP391.9; V351

Recommended Citation

Tao Yifei, Ding Xiaopeng, Luo Junbin, et al. Simulation Optimization of Airport Baggage Import System Based on Multi-objective Wolf Pack Algorithm[J]. Journal of System Simulation, 2024, 36(7): 1655-1669.

Corresponding Author

Ding Xiaopeng

DOI

10.16182/j.issn1004731x.joss.23-0437