Research On The Optimization Of Belly Loading Of Civil Aviation Wide Body Airliner

With the vigorous development of the aviation industry,the number of wide body airliners put into operation is increasing day by day,and Abdominal compartment of aircraft has become the main transport capacity of air cargo.Under the background of the combination of passenger and cargo,it is of great theoretical and practical significance to study how to ensure the safety of the belly stowage,how to improve the efficiency of the load,how to improve the utilization of the container and the belly space,so as to reduce the cost of air cargo and improve the comprehensive efficiency of air transportation.Firstly,this paper introduces the research background and significance of the belly loading problem of the wide body airliner,summarizes the research on the loading space problem,the loading model and the solution algorithm according to the domestic and foreign literature,and clarifies the three-dimensional packing problem for the belly loading of the civil aviation wide body airliner,taking the comprehensive load utilization ratio and the volume utilization ratio as the double optimization objectives,through the first series Based on the combination of heuristic algorithm and hybrid genetic particle swarm optimization,this paper studies the optimization of the belly loading problem of civil aviation wide body airliner,and achieves the following two innovative results.(1)In view of the problem of cargo loading optimization in the belly compartment of airliner,most scholars only consider the loading problem of cargo,ignoring the loading factor of passenger’s checked baggage,which makes the previous research have some limitations.At the same time,this paper considers the problem of luggage loading and cargo loading,and sets up a reasonable loading sequence for comprehensive optimization to fill the gap left by the problem of cargo loading in the belly of the airliner.(2)Aiming at the complex problem of cargo loading in the belly of airliner,combining the advantages of heuristic algorithm,genetic algorithm and particle swarm optimization algorithm,a "heuristic algorithm + hybrid genetic particle swarm optimization algorithm" is jointly developed and designed.The heuristic algorithm is used to determine the initial population of the optimization algorithm,and the hybrid GAPSO,which combines the dual optimization particle swarm optimization and genetic algorithm,is used as the core optimization algorithm.It not only prevents the local optimization of the particle swarm optimization algorithm,but also overcomes the disadvantage that the genetic algorithm is easy to fall into precocity.By coding the particles in the way of DNA sequence,and introducing The cross mutation mechanism of genetic algorithm makes the joint algorithm obtain good improvement and optimization effect.Finally,the HGPSO algorithm is programmed by MATLAB,and then the optimal model and algorithm of belly loading are solved by an example.The result shows that the utilization rate of luggage loading space is 95.2%,the utilization rate of cargo loading space is 85.8%,91.6% and 82.4% respectively.An example shows that the improved algorithm is effective.