Optimization method of personnel allocation plan for apron cargo support

BI Jun; HUI Jing; CHENG Pei-xuan; WANG Yong-xing

doi:10.19818/j.cnki.1671-1637.2025.04.018

Volume 25 Issue 4

Aug. 2025

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BI Jun, HUI Jing, CHENG Pei-xuan, WANG Yong-xing. Optimization method of personnel allocation plan for apron cargo support[J]. Journal of Traffic and Transportation Engineering, 2025, 25(4): 254-266. doi: 10.19818/j.cnki.1671-1637.2025.04.018

Citation:

BI Jun, HUI Jing, CHENG Pei-xuan, WANG Yong-xing. Optimization method of personnel allocation plan for apron cargo support[J]. Journal of Traffic and Transportation Engineering, 2025, 25(4): 254-266. doi: 10.19818/j.cnki.1671-1637.2025.04.018

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Optimization method of personnel allocation plan for apron cargo support

doi: 10.19818/j.cnki.1671-1637.2025.04.018

1.
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
2.
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China

Funds:

National Natural Science Foundation of China 72171019

Received Date: 2024-11-20
Accepted Date: 2025-04-02
Rev Recd Date: 2025-02-05
Publish Date: 2025-08-28

Abstract

Abstract

To enhance the efficiency of air cargo support operations, optimize the allocation of apron cargo support personnel, and ensure the efficient operation and timeliness of air cargo services, a scientifically optimized method that balances human resource optimization and task distribution was proposed. Based on the demand characteristics of the air cargo business, the composition of the apron cargo support personnel groupings was designed. By fully considering the constraints related to the apron cargo support processes, an optimization model for the apron cargo support personnel allocation plan was built. The objective was to minimize the total number of human resources and balance the task load. In line with the characteristics of the model, a task allocation optimization strategy was proposed to enhance the chromosome search direction, and an improved genetic algorithm was subsequently developed to solve the model efficiently. A numerical case study based on actual operational data from a domestic airport was conducted to verify the feasibility and effectiveness of the proposed model and algorithm. The results show that, compared with the traditional genetic algorithm, the proposed improved genetic algorithm significantly enhances the resource utilization rate. The total number of apron cargo support personnel is reduced from 44 to 28, and the human resource utilization rate is increased by 36.36%. In addition, compared with the results obtained directly from the Gurobi solver, the improved genetic algorithm maintains a high level of accuracy while demonstrating a clear advantage in computational efficiency. The Gurobi solver takes 112.28 s to obtain a solution, whereas the improved genetic algorithm requires only 11.17% of that time. The proposed optimization method can reduce redundant configurations and optimize the distribution of personnel task load in a multi-task and multi-constraint dynamic environment. It provides a scientific and efficient solution for the problem of the allocation of air cargo support personnel.
- air cargo,
- apron cargo support personnel,
- allocation plan,
- improved genetic algorithm,
- task allocation optimization,
- human resource,
- task balancing

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References

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Optimization method of personnel allocation plan for apron cargo support

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