Abstract: For the real-time warehousing logistics vehicle scheduling problem（LVCP）, an RFID- enabled vehicle dynamic scheduling algorithm based on Immune Glowworm Swarm Optimization Algorithm（IGSOA） is proposed. A mathematical model for Vehicle Routing Problem（VRP） with delivery cost is established, and the IGSOA is used to solve this model. IGSOA combines the GSO and CSA technology, and adopts a multi-layer evolution pattern. The polymorphic adaptive population mechanism and global extreme screening strategy are introduced in the low GSO operation and high immune operation, in order to improve the IGSOA convergence efficiency. Based on above analysis, a vehicle dynamic scheduling framework is presented, and the vehicle dynamic scheduling process is divided into two stages as vehicle scheduling tasks control and VRP optimization. The process of LVCP is given. Experimental results show that, the IGSOA can effectively solve large-scale LVCP.

Key words: logistic distribution, optimizing routing, glowworm swarm optimization algorithm, immune algorithm, dynamic scheduling

摘要： 针对物流配送实时仓储车辆调度问题，提出了一种基于RFID技术的免疫萤火虫车辆动态调度框架。建立了基于配送成本的带约束条件车辆路径问题数学模型，运用免疫萤火虫优化算法求解该模型，免疫萤火虫优化算法将萤火虫优化及免疫克隆技术融合，采用多层进化模式，在低层萤火虫操作中及高层免疫操作中分别引入多态子种群自适应机制和全局极值筛选策略，以提高算法全局收敛效率，在此基础上设计了仓储车辆动态调度框架，将车辆动态调度过程分为车辆调度任务控制和路径优化两个阶段，给出了车辆动态调度任务处理流程。实验仿真表明，该车辆动态调度算法能够有效地解决大规模动态物流车辆调度问题。

关键词: 物流配送, 路径优化, 萤火虫优化算法, 免疫算法, 动态调度