摘要
针对物流配送中车辆路径的问题,提出一种烟花算法结合遗传算法的物流配送异质车队路径优化方法;根据优先聚类其次路径的两阶段构造理论将新型群体智能算法烟花算法与遗传算法进行有效结合,首先按运力空间划分聚类区域,并采用改进的遗传算法解决为客户分配车辆的问题,然后通过采用烟花算法对路径排序实现本地路径优化;将该方法的实验结果与经验结果进行了比较,结果表明,所提出的混合算法模型得到的实验结果优于经验结果。
Aiming at the problem of vehicle routing in logistics distribution,this paper presents a method of route optimization for heterogeneous fleet of logistics distribution based on fireworks algorithm and genetic algorithm.According to“clustering first routing second”priority two-phase structure theory of the path will be a new swarm intelligence algorithm fireworks algorithm combined with genetic algorithm is effective.firstly,according to the capacity space partition clustering area,and uses the improved genetic algorithm solve the problem of allocation of vehicles for customers,and then by using the algorithm of fireworks to sort to realize local path optimization.The experimental results are compared with the empirical results,and the experimental results show that the proposed hybrid algorithm model is superior to the empirical results.
作者
庞凌
Pang Ling(Liaoning Vocational College of Equipment Manufacture,Shenyang 110161,China;Liaoning Radio and TV University,Shenyang 110161,China)
出处
《计算机测量与控制》
2019年第8期245-248,共4页
Computer Measurement &Control
基金
中国物流学会基金项目(JZW2016129)
关键词
烟花算法
聚类
遗传算法
车辆路径
利用率
物流配送
fireworks algorithm
clustering
genetic algorithm
vehicle routing
utilization
logistics distribution