Research On Capacity Inventory Control Of Air Cargo

With the rapid development of air cargo and the increasing competition of logistics market, revenue management has become the important means of increasing revenue and competitiveness. Similar to airline industry, air cargo has the potential characteristics for the application of revenue management. However, there are some differences in sales pattern and marketing environment between cargo transportation and passenger transportation. So the study on the capacity inventory control of air cargo industry has great significance. Based on the analysis of air cargo revenue management, the problem of capacity inventory control in uncertain environment is researched, so that some basis can be provided method support for applying of air cargo revenue management.Firstly, through analyzing the current situation and characteristics of air cargo, the necessity of research on air cargo revenue management is pointed out. And, based on discussion of the structure of air cargo revenue management system and the process of capacity inventory control, the uncertain factors and optimizing criterion of slot allocation are studied.Secondly, due to the fierce market competition and the complex decision-making environment, decision-making capability of airline companies has become an important factor of revenue management. In order to reflect the influence degree of uncertainties for capacity inventory control and satisfy the needs of different decision-makers, a robust capacity allocation model for a multiple-leg with multiple shipment types is established,which describe uncertainty of these parameters as a number of discrete scenarios, and obtain the optimal allocation with mutation particle swarm optimization. Compared with determinate programming method, the simulation experiments show that this method can balance uncertainty of the model effectively and accord with actual situation.Finally, based on the study of the model of pre-chapters, expresses the uncertainty prices of retail-products and uncertainty demands as ellipsoids. And based on ellipsoid sets, the robust capacity allocation model is proposed. To deal with the pre-maturity of canonical genetic algorithm, niche genetic algorithm is adopted. Experimental results show the algorithm can improve the search ability and convergence rate, and the model has the certain superiority in the capacity inventory control.