不确定条件下航路点布局优化研究  

Optimization study of crossing waypoints location under uncertainty

作　　者：严伟 王瑛[1] 孟祥飞[1] 张文倩[1] 亓尧 Yan Wei;Wang Ying;Meng Xiangfei;Zhang Wenqian;Qi Yao(College of Equipment Management ＆ Security Engineering,Air Force Engineering University,Xi＇an 710051,China)

机构地区：[1]空军工程大学装备管理与安全工程学院,西安710051

出　　处：《计算机应用研究》2018年第8期2338-2341,2350,共5页Application Research of Computers

摘　　要：航路网络(air route network,ARN)是支撑飞行器安全高效飞行的载体,是空中交通的基础。针对航路网络的运行成本和安全性相冲突问题,同时考虑到需求、天气和科技发展三类不确定因素影响,对航路点布局问题(crossing waypoints location problem,CWLP)建立了不确定条件下的多目标优化模型,求解时首先将模型中不确定变量进行期望值处理,将不确定问题确定化,再选取随机权重策略的粒子群优化(particle swarm optimization,PSO)算法,根据决策者的偏好分配目标权重进行处理。最后以北京飞行情报区进行仿真对比,得到了平滑均匀的非支配解,实现了航路点的布局设计。并将优化后的网络与原始网络相比,数据显示在成本和冲突系数上分别有不同程度的改善。实验结果证明此方法能够给决策者提供多种优化方案,并为在不确定因素影响下设计航路网络提供一种思路。The air route network（ARN）, the basic of air traffic system, is the carrier of supporting secure and efficient flight of aircraft. In respond to the conflict of the operational cost and the security, and taking three kinds of uncertainty factors—the demand for services, the weather and the development of technology into account, this paper built the model of multi-objective optimization for crossing waypoints location problem（CWLP） under uncertainty. In the solution, first of all, it treated the uncertain variables and gained their expected values respectively, turning the uncertainty into certainty. Then, it adopted particle swarm optimization algorithm with random weight to solve the problem, and distributed the object weight reasonably according to the decision makers’ preference for the objective function. Finally, it chose Beijing flight information region to simulate, obtaining the smooth and uniform non-dominated solution, and implemented the design of crossing waypoints location. In addition, comparing the optimized network with the original, the data shows that the cost and the conflict coefficient, respectively, can have different improvements. The experimental results indicate that the method can offer various solutions for the decision makers and provide an idea for air route network design under the effect of uncertain factors.

关 键 词：航路点布局 不确定因素 粒子群算法 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]