基于新型细菌觅食优化算法的飞机动态泊位问题

Novel bacterial foraging optimization algorithm for dynamic aircraft parking stand allocation problem

随着航空运输业的发展,传统手动设计泊位方案已难以满足日益增长的外包维修需求.在外包模式下,如何快速给出高效的动态泊位方案关系到维修任务订单的准点交付,是飞机维修服务公司亟待解决的重要问题.针对飞机泊位进出顺序及碰撞检测特点,构建带时间窗的飞机维修泊位模型.设计自适应趋化学习及交叉协作策略,提出新型细菌觅食优化算法,并设计一系列约束处理机制.研究结果表明,提出的基于矩形碰撞检测方法可有效预防并判断飞机间碰撞阻塞情况.新型细菌觅食优化算法在解决飞机动态泊位问题上展现出搜索精度高、稳定性强等特点.所得高效智能化泊位调度方案有助于在保证维修安全的情况下提升飞机维修服务提供商的维修服务效率,改进维修资源利用率与维修系统的柔性,为企业实现高质量发展打下良好基础.

With the rapid development of the aviation industry,traditional manual aircraft parking stand allo-cation method cannot satisfy the increasing maintenance demands.To guarantee the punctual delivery of out-sourcing maintenance task orders,how to provide efficient dynamic aircraft parking stand allocation scheme becomes an urgent problem.This paper proposes a novel bacterial foraging optimization algorithm with self-adaptive learning method and cross-collaboration strategy.Moreover,constraint handling mechanism is subtly designed for each hard constraint.Results indicate that the rectangular collision detection method can effective-ly prevent and judge the collision and blocking situation between aircrafts.Meanwhile,experimental results demonstrate the superiority of our designed algorithm on dynamic aircraft parking stand allocation problem.Furthermore,the intelligent allocation schemes can help to improve the efficiency and theflexibility of main-tenance process while ensuring maintenance safety,laying a good foundation for high-quality development.