基于启发式算法的支线货机配载优化研究  

Optimization of Regional Freighter Aircraft Loading Based on Heuristic Algorithms

作　　者：张昕喆 余彬 张潜锐 李国举 ZHANG Xinzhe;YU Bin;ZHANG Qianrui;LI Guoju(School of Aerospace Engineering,Zhengzhou University of Aeronautics,Zhengzhou 450046,China;Henan Provincial Key Laboratory of General Aviation Technology,Zhengzhou University of Aeronautics,Zhengzhou 450046,China)

机构地区：[1]郑州航空工业管理学院航空宇航学院,河南郑州450046 [2]郑州航空工业管理学院河南省通用航空技术重点实验室,河南郑州450046

出　　处：《郑州航空工业管理学院学报》2025年第2期52-58,66,共8页Journal of Zhengzhou University of Aeronautics

基　　金：国家自然科学基金(52206059);河南省通用航空技术重点实验室开放基金(ZHKF-230202);2024年郑州航院研究生教育创新计划基金项目(2024CX69);河南省高等学校重点科研项目计划(25A590002)。

摘　　要：针对支线货机多约束目标条件下超窄体货舱的非确定性货物配载问题,建立支线级航空货运配载数学模型,采用改进的遗传算法和模拟退火算法两种启发式算法对配载模型进行求解。以新型支线货机ARJ21-700F的配载过程为研究目标,将最大配载率和最小重心偏移量作为优化目标,进行15组配载方案的优化求解。对结果进行对比发现:遗传算法在求解配载模型时表现出较好的稳定性和优化结果,而模拟退火算法则表现出较高的求解效率。所建立的支线级航空货运配载模型在启发式算法的求解下,保证重心偏移量在安全范围内,货物配载率均在88%以上,并且配载时间不超过2.5 s,有效提升了支线航空货运配载的安全性和高效性。To address the non-deterministic cargo loading challenge within the ultra-narrow body cargo compartments of regional freighter aircraft under a multitude of constraints,a mathematical model for regional freighter aircraft loading is established, and two improved heuristic algorithms—Genetic Algorithm(GA) and Simulated Annealing Algorithm(SAA) are applied for optimization. Taking the ARJ21-700F regional freighter's loading process as a case study, the optimization aims to maximize the cargo loading rate while minimizing center of gravity offset. A total of 15 loading schemes are optimized, revealing that GA excels in stability and optimization performance, whereas SAA demonstrates higher solution efficiency. The heuristic algorithms ensure that the center of gravity offset remains within safe limits, the cargo loading rate exceeds 88%, and the loading time is within 2.5 seconds. This study significantly enhances the safety and efficiency of regional air cargo loading.

关 键 词：遗传算法 模拟退火算法 支线货机 配载平衡 配载效率 

分 类 号：U169[交通运输工程]