基于模糊需求的生鲜配送路线多目标优化问题研究  

Research on Multi-objective Optimization Problem of Fresh Food Delivery Route Based on Fuzzy Demand

作　　者：吴迪 崔艺漩 WU Di;CUI Yixuan(School of Management,Hebei GEO University,Shijiazhuang 050000,China)

机构地区：[1]河北地质大学管理学院,河北石家庄050000

出　　处：《物流科技》2024年第24期163-168,共6页Logistics Sci Tech

基　　金：河北省高等学校人文社会科学研究项目(SQ2023238)。

摘　　要：随着电商行业的深入快速发展,连锁超市生鲜产品的运输时效性面临着越来越严峻的挑战,如何合理规划配送路线,减少迂回线路、提高运输效率,成为各大连锁超市必须解决的关键问题。建立混合蚁群算法模型,将该模型与改进Kmeans聚类相结合,并且考虑生鲜需求的模糊性,引入模糊需求变量,在制定配送方案时应对需求的波动和不确定性,以物流成本和货损成本最小为目标函数,考虑生鲜食品变质腐败过程是一个指数型变质腐败过程,对模型进行规划求解。最后以北国超市生鲜配送业务为例进行对比分析,发现新的配送方案能够有效减少配送成本,提高配送效率。混合蚁群算法有助于优化配送资源的利用,包括车辆的合理调度和货物的合理分配,减少资源浪费。With the deep and rapid development of the e-commerce industry,the transport timeliness of fresh products in super-market chains is facing more and more severe challenges,so how to reasonably plan distribution routes,reduce circuitous routes and improve transport efficiency,which has become a key problem that major supermarket chains have to solve.A hybrid ant colony algorithm model is established,combining the model with improved K-means clustering,and considering the fuzzy demand for fresh food,fuzzy demand variables are introduced to cope with the fluctuation and uncertainty of the demand in the formulation of the distribution plan.And with the objective function of minimizing the cost of logistics and the cost of damage to the goods,considering that the process of deterioration and corruption of fresh food is an exponential process of deterioration and corruption,and planning and solving of the model is carried out.Finally,the fresh food distribution business of Beiguo Supermarket is taken as an example for comparative analysis,and it is found to be able to effectively reduce the distribution cost and improve the distribution efficiency.The hybrid ant colony algorithm helps to optimise the use of distribution resources,including the reasonable scheduling of vehicles and the reasonable distribution of goods,and reduce the waste of resources.

关 键 词：生鲜配送 模糊需求 混合蚁群算法 

分 类 号：F252[经济管理—国民经济]