基于群体增量学习算法的第三方物流网络设计

Network Design of Third-Party Logistics Based on Population Based Incremental Learning Algorithm

研究第三方物流(3PL)网络设计问题,建立柔性运输模式下的3PL网络设计优化模型,通过选择开设3PL仓库和3PL物流中心使总物流成本最小。根据问题模型设计群体增量学习(PBIL)算法,采用0/1编码方式对个体进行编码,并将需求满足约束作为惩罚项加入到个体评价函数中进行处理。最后,通过仿真实验来验证模型的合理性及PBIL算法的有效性。

The problem of network design of the third-party logistics（3 PL） is studied. An optimization model of 3 PL network design under flexible transportation mode is proposed, which minimizes the total logistics costs by selecting the 3 PL warehouses and logistics centers to open. A population based incremental learning（PBIL） algorithm is developed, which represents the individual by 0/1 coding method, and handles the demand satisfaction constraints by combining them into the evaluation function of the individual as the penalty terms. Finally, numerical experiments are presented and the results indicate the validity of the model as well as the effectiveness of the proposed PBIL algorithm.