基于改进遗传算法的最小油耗机场飞行区布局优化

doi:10.3969/j.issn.1674-0696.2022.12.07

摘要/Abstract

摘要： 为降低机场飞行区的飞机燃油消耗，根据飞行区的结构特点，完成了改进遗传算法设计，并针对停机位分配和飞行区布局开展了优化研究。通过对飞行区跑道、滑行道、联络道及停机坪位置和停机位分布形式的分析，在考虑不同机型飞机油耗的基础上，建立了单跑道飞行区构型以及直线式停机位分布形式的飞行区油耗仿真模型，以飞行区油耗最低为优化目标，完成适应度函数设计；设计了一种实数编码和二进制编码混合编码方式，可兼顾停机位分配和飞行区结构参数的编码需求；完成混合编码基因到可行解的映射以及基因选择、交叉和变异的进化操作设计；采取惩罚函数的方法，减小进化过程中不可行解基因对可行解基因的影响；采用最优保存策略，以保证最优个体基因在进化操作过程中不被破坏，提高遗传算法优化的效率和准确度；为验证优化方法的有效性，对飞行区构型为一跑一滑和停机位分布形式为直线式的飞行区进行了优化。优化结果表明：经改进后的遗传算法可有效对飞行区参数进行优化，以实现飞机油耗最低的目的，优化收敛速度快、质量高。

关键词: 航空运输工程；节能；改进遗传算法；停机位分配；飞行区布局

Abstract: To achieve a reduction of aircraft fuel consumption at the airport flight area, according to the structural characteristics of the airport flight area, an improved genetic algorithm design was completed, and optimization studies were carried out for the airport stand allocation and flight area layout. Through the analysis of the location of runway, taxiway, connecting lane and apron in the airfield area and the distribution form of parking stands, based on the fuel consumption of different types of aircraft, the fuel consumption simulation model of airport airfield with the configuration of single runway and linear parking lot distribution was established. Taking the minimum fuel consumption in airfield as the optimization objective, the fitness function design was completed. A mixed coding method of real number coding and binary coding was designed, which could meet the needs of both the aircraft stand allocation and the coding of the structural parameters of the flight area. The mapping of mixed coding genes to feasible solutions and the design of evolutionary operations for gene selection, crossover and mutation were completed. Penalty function was used to reduce the influence of infeasible genes on feasible genes in the evolution process. The optimal preservation strategy was adopted to ensure that the optimal individual gene was not destroyed in the evolution process, and the efficiency and accuracy of genetic algorithm optimization was improved. In order to verify the effectiveness of the proposed optimization method, the airfield with one runway one taxiway configuration and straight-line stand distribution was optimized. The optimization results show that: the improved genetic algorithm can be used to effectively optimize the parameters of the airfield to achieve the minimum fuel consumption of the aircraft, with fast convergence speed and high quality.

Key words: air transport engineering; energy conservation; improved genetic algorithm; stand allocation; airfield layout

中图分类号:

V351.11

李汝宁1，冯兴2. 基于改进遗传算法的最小油耗机场飞行区布局优化[J]. 重庆交通大学学报（自然科学版）, 2022, 41(12): 48-55.

LI Runing1, FENG Xing2. Flight Area Layout Optimization of Airfield with Minimum Fuel Consumption Based on Improved Genetic Algorithm[J]. Journal of Chongqing Jiaotong University(Natural Science), 2022, 41(12): 48-55.

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