Research on line maintenance personnel configuration at the airline base of civil aviation based on a dual-objective approach

Purpose To improve personnel utilization, avoid waste of human resources and ensure fair distribution of workload, and at the same time comply with the operation regulations of the airlines maintenance department, this article aims to propose a two-objective optimization model for scheduling line maintenance personnel at airline base stations and innovatively considers maintenance personnel qualification while aiming to minimize labor costs and fairly distribute workloads to meet the actual situation of the maintenance team. Design/methodology/approach The article uses an improved bacterial foraging optimization (BFO) algorithm based on structural reorganization and biological learning strategies to solve the complex optimization model. This approach is validated through comparative experiments with traditional heuristic algorithms, assessing its effectiveness and reliability. Findings The experimental results show that the improved bacteria foraging optimization algorithm is better than the traditional heuristic algorithm in terms of solving accuracy and stability, and the model meets the actual needs of airline line maintenance. Originality/value The model can automate the scheduling of maintenance personnel, significantly reduce the total operational costs of line maintenance management and ensure equitable workload distribution, which has potential practical application in the line maintenance department of airlines.