基于遗传算法的物流无人机控制矫正研究

Research on Control and Correction of Logistics UAV Based on Genetic Algorithm

文章研究了城市环境下异构物流无人机的调度问题,与传统的车辆路径问题不同的是,它引入了一些新的特性,例如负载能力、最大飞行时间和飞行速度等。作为一个变体,所考虑的调度问题被认为是一个非确定性多项式问题。首先,文章建立了具有异构设置的无人机调度问题模型。其次,提出了一种基于遗传算法的调度问题求解框架,该框架对编码/解码方法、初始种群生成方法和遗传操作进行了精细设计。为了减少搜索空间,加快算法的执行速度,采用基于权重的加载方法。为了进行性能评估和统计分析,文章将该算法与现有的两种算法进行比较。实验结果表明,该算法能有效地解决该问题。

This paper studies the scheduling problem of heterogeneous logistics UAV in the urban environment.Unlike the traditional vehicle routing problem,it introduces some new characteristics,such as load capacity,maximum flight time and flight speed.As a variation,the scheduling problem is considered to be a nondeterministic polynomial problem.Firstly,a model of UAV scheduling problem with heterogeneous settings is established.Secondly,a scheduling problem solving framework based on genetic algorithm is proposed.The framework has fine design for encoding and decoding method,initial population generation method and genetic operation.In order to reduce the search space and speed up the execution of the algorithm,a weight based loading method is used.For performance evaluation and statistical analysis,this algorithm is compared with two existing algorithms.Experimental results show that the algorithm can effectively solve this problem.