基于动态遗传算法的共享配送模式研究

针对传统配送中配送车辆装载率低、车辆数量多及配送成本高等问题,提出不同类型零售商资源共享的城市配送优化方法,并考虑配送中的车辆油耗与不确定需求等问题。以总配送成本最低为目标建立模型,利用基于动态参数的改进遗传算法对模型进行求解。最后,通过算例对共享配送模式与算法进行测试。结果表明,共享配送模式能够有效减低车辆数量、提高装载率及降低配送成本,同时改进遗传算法能够高效、准确对模型求解。

Study of Sharing Distribution Model Based on Dynamic Genetic Algorithm

Aiming at issues of low loading rate, large number of distribution vehicles,and high cost of distribution, wecome up with an optimization pattern of urban distribution, which is based on resource sharing between different retailers. Taking fuel consumption and uncertain demand into account, and setting minimizing total cost of distribution as the objective,we build the model and use improved genetic algorithm, which are based on dynamic parameters, to solve the model. Finally, wetest the delivery method under resource sharing and algorithm by numerical example. The result shows that the sharing delivery method can reduce the number of vehicles, improve loading rate and cut the cost of distribution effectively, and at the same time, the improved genetic algorithm can solve the model efficiently and accurately.