Optimisation and improvement of transportation assembly model of civil aviation cargo aircraft

• Main Author: Jing Zhang
• Format: Article
• Language: English
• Published: Wiley 2019-08-01
• Series: The Journal of Engineering
• Subjects: logistics; genetic algorithms; assembling; transportation; aircraft; civil aviation cargo aircraft assembly; fixed crossover; mutation probabilities; improved genetic algorithm; optimisation; cargo aircraft transportation assembly model; volume utilisation ratio; transport assembly model; civil aviation cargo industry; limited loading space; civil aviation aircraft companies; loading rate
• Online Access: https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0987

The rise of civil aviation cargo industry has greatly increased the speed of global logistics, and the relatively high cost and limited loading space of civil aviation aircraft determines that civil aviation aircraft companies need to optimise the cargo assembly scheme to achieve the high loading rate under the limited cost. This study briefly introduced the mathematical model and genetic algorithm of civil aviation cargo aircraft assembly and improved the fixed crossover and mutation probabilities of genetic algorithm to adaptive crossover and mutation probabilities. Then two algorithms were simulated and analysed in MATLAB software. The results showed that the improved genetic algorithm converged faster in the optimisation of cargo aircraft transportation assembly model and had higher adaptability after stabilisation. In terms of load and volume utilisation ratio of cargo hold, the assembly scheme optimised by the improved genetic algorithm has higher load and volume utilisation ratio. In conclusion, the improved genetic algorithm is suitable for the optimisation of the transport assembly model of civil aviation cargo aircraft.