Study Of Scheduling Optimization Of Single ETV In Jumbo Airport Cargo Terminal

At the age of economic globalization, owing to the development of information technology and e-commerce, air cargo is occupying occupies an increasingly important position in the respect of economics, and great opportunities and severe challenges also has have been brought to the relevant industries and scientific research researcher in the field of air cargo sector, in the era of economic globalization. As the third profit source, airport cargo logistics plays a more and more important role for enterprises to reduce costs. However, the efficiency of cargo handling in air cargo terminal is the main factor that restricts the efficiency of air freight. Almost all air cargos are carried by unit load device. Most of cargo is handled in containerized storage, whose efficiency is one of important step to influence the efficiency of airport cargo terminal. At the same time, the efficiency of containerized storage is affected by Elevating Transfer Vehicle(ETV), which is core logistics equipment in containerized storage.In this paper, the main work is to improve the processing efficiency of containerized cargo by improving scheduling efficiency of ETV. Thereby, facilitating the whole efficiency of airport cargo terminal to be increased.By referring to a large number of relevant literature and combining with practice, the paper studied the character of containerized storage and the special process to dispatch ETV.Based on this thinking, the mathematical model is established and solved by genetic algorithm.Simulation results show that the proposed method can improve the working efficiency of ETV. At the same time,enhancing the efficiency of containerized storage and airport cargo terminal.This dissertation mainly includes:Analysis the problem of library scheduling in containerized storage, in order to solve this problem, the problem is abstracted and concluded as the permutation flow shop scheduling problem. And then, building the mathematical model based on the shortest delivery time under the single ETV working environment.Through comparative analysis, the scheduling problem is solved by using genetic algorithm. Improves the crossover operator and mutation operator of standard genetic algorithm. It is helpful to avoid precocity. Furthermore, its effectiveness is verified by typical test functions.In this dissertation, taking the actual operation of a large airport as an example, the improved adaptive genetic algorithm is used to optimize the scheduling. The final simulating result shows that this method is fairly efficient in the optimization of the scheduling of the delivery of cargo from airport cargo terminal. Compared with traditional mode of operation. Itcan effectively enhance the delivery speed of container goods. Engineering requirements can be meet by this method. So it has good engineering value and theoretical value.