自适应精英遗传算法的快递车路径规划

Path planning of express vehicle based on adaptive elite genetic algorithm

针对快递车物流配送效率低、行驶路线不规范的问题,提出了自适应精英遗传算法实现对快递车的路径规划。通过搭建车载定位系统,实时对车辆位置进行监督以确保行驶在规定路线上。在实际快递位置分布的基础上建立了路径规划模型,设计了基于经纬度坐标的适应度函数,以地表距离作为种群评价标准更加贴合实际运输需求;引入自适应交叉算子和自适应变异算子,根据个体基因的适应度值自适应地调节交叉和变异概率,并将精英个体进行遗传保留,更好地平衡了算法的局部搜索能力和全局优化性能。通过与其他4种智能算法的对比实验,来验证改进算法的有效性及可行性,实验结果表明改进算法的收敛性最快且解的精度明显优于其他4种算法。

Aiming at the problem of low logistics distribution efficiency of express vehicles and irregular driving routes,an adaptive elite genetic algorithm was proposed to realize the path planning of express vehicles.By building a vehicle-mounted positioning system,the vehicle position was monitored in real time to ensure that it was driving on a prescribed route.A path planning model was established on the basis of the actual express location distribution,and a fitness function based on latitude and longitude coordinates was designed,and the ground distance was used as the population evaluation criterion to better fit the actual transportation needs;adaptive crossover operator and adaptive mutation operator were introduced according to the fitness value of individual genes,adaptively adjusted the crossover and mutation probability,and retained the elite individuals genetically,which better balanced the local search ability and global optimization performance of the algorithm.Through comparative experiments with other four intelligent algorithms,the effectiveness and feasibility of the improved algorithm were verified.The experimental results showed that the improved algorithm had the fastest convergence and the accuracy of the solution was significantly better than the other four algorithms.