CAJ | 학술논문

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。
침대물류배송실시창저차량조도문제，제출료일충기우RFID기술적면역형화충차량동태조도광가。건립료기우배송성본적대약속조건차량로경문제수학모형，운용면역형화충우화산법구해해모형，면역형화충우화산법장형화충우화급면역극륭기술융합，채용다층진화모식，재저층형화충조작중급고층면역조작중분별인입다태자충군자괄응궤제화전국겁치사선책략，이제고산법전국수렴효솔，재차기출상설계료창저차량동태조도광가，장차량동태조도과정분위차량조도임무공제화로경우화량개계단，급출료차량동태조도임무처리류정。실험방진표명，해차량동태조도산법능구유효지해결대규모동태물류차량조도문제。
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.