基于蚁群-免疫算法的组团弹性物流配送优化

Dynamic Optimization of Distribution Route of Tobacco Group Logistics Based on Ant Colony Immune Algorithm in Elastic Mode

为有效降低烟草配送成本,从配送与补货角度,提出组团式新型物流配送模式。结合位置、需求与补货周期等信息,将需求点按小组划分,建立了组团弹性配送优化模型。以配送路径最短为目标,设计了组团弹性模式下的蚁群-免疫算法,实现了对配送路径的优化和仿真。通过实验例证和对比分析,验证了模型可行性与算法的有效性。

In order to effectively reduce the cost of tobacco distribution,this article innovates,from the perspective of distribution and replenishment,a new group-based logistics distribution model.With information such as location,demand and replenishment cycle combined,the demand points are divided into groups,and a group flexible distribution optimization model is established.With the aim for the shortest delivery path,an ant colony-immune algorithm under the group elastic mode is designed to realize the optimization and simulation of the delivery path.Finally,the feasibility of the model and the effectiveness of the algorithm are verified through experimental examples and comparative analysis.