摘要
传统快递末端配送模式存在快递网点建设冗余、派送路径重叠等问题,而共同配送模式可有效解决此类问题,因此对共同配送模式下同时收派件且收件需求为不确定情形的快递末端网点选址路径问题进行研究。首先,建立了两阶段数学优化模型,引入随机机会约束来处理收件量不确定的问题。其次,设计基于遗传算法和自适应大邻域搜索算法的混合启发式算法。最后,通过数值实验表明:所设计的混合算法比传统遗传算法具有较快的收敛速度和较好的求解质量;决策者对随机需求下的优化方案风险接受程度过高或过低都会导致成本上升;随客户收派量之比的增加,快递末端配送成本呈先降低后增高的趋势;采用最近网点返回策略可有效降低企业配送成本。
The traditional express terminal distribution mode has problems such as redundant construction of express outlets and overlapping delivery paths,and the joint distribution model can effectively solve these problems.Therefore,this paper studies the location path of express terminal outlets in the case of simultaneous receiving and dispatching and uncertain receiving demand under the joint distribution model.Firstly,a two-stage mathematical optimization model is established to deal with the problem of uncertain receipt volume by introducing random chance constraints.Secondly,a hybrid heuristic algorithm based on genetic algorithm and adaptive large neighborhood search algorithm is designed.Finally,numerical experiments show that the designed hybrid algorithm has a faster convergence speed and better solution quality than the traditional genetic algorithm.Too high or low risk acceptance of the optimization scheme in the random demand environment will lead to the increase of cost.With the increase of the ratio of customer receiving and dispatching volume,the cost of express terminal distribution first decreases and then increases,The nearest outlet return strategy can effectively reduce the distribution cost of enterprises.
作者
孙睿男
初翔
陈昱
闫明宁
SUN Rui-nan;CHU Xiang;CHEN Yu;YAN Ming-ning(School of Shipping Economics and Management,Dalian Maritime University,Dalian 116026;Comprehensive Transportation Collaborative Innovation Center,Dalian Maritime University,Dalian 116026,China)
出处
《计算机工程与科学》
CSCD
北大核心
2024年第1期159-169,共11页
Computer Engineering & Science
关键词
共同配送
选址路径问题
遗传算法
自适应大邻域搜索算法
快递网点
joint distribution
location routing problem
genetic algorithm
adaptive large neighborhood search algorithm
express outlets
