基于空间映射遗传算法的烟草仓储垛位分配策略研究  

Study on Warehouse Location Allocation Strategy for Tobacco Based on Spatial Mapping Genetic Algorithm

作　　者：孙小涵 奚家勤[2] 彭勇刚[1] 贾桥东 Sun Xiaohan

机构地区：[1]浙江大学电气工程学院,浙江杭州310027 [2]中国烟草总公司郑州烟草研究院,河南郑州450001 [3]浙江中烟工业有限责任公司,浙江杭州310000

出　　处：《工业控制计算机》2024年第9期12-14,16,共4页Industrial Control Computer

基　　金：中国烟草总公司重点研发项目“烟叶原料智慧物流关键技术研究及应用”(110202202044)。

摘　　要：烟叶原料的仓储物流是烟草行业的核心环节之一,针对当前烟叶原料入库的垛位分配完全依赖保管员人工经验,智能化程度较低的问题,对烟叶原料入库分配过程建立空间模型及任务模型,提出了一种基于空间映射遗传算法的烟草仓储垛位分配策略。该模型将烟叶原料出入库效率、醇化质量、同类原料离散度及库容利用率作为评价指标,采用空间映射遗传算法对目标函数进行整体寻优,得到符合烟叶原料仓储物流规律的高效分配计划。仿真结果表明,该研究提出的模型及算法在暂存烟入库任务、新烟入库任务和混合入库任务三种任务类型上表现良好,并在混合入库任务算例上与传统策略进行对比,证明了该策略对优化烟叶原料垛位分配、解除对人工的依赖具有显著效果。This research aims at the problem that the current stack allocation of tobacco leaf raw materials into the warehouse is completely dependent on the manual experience of the custodians,and the degree of intelligence is low.Model and task model,a tobacco storage location allocation strategy based on spatial mapping genetic algorithm is proposed in this paper.The model takes tobacco raw material storage efficiency,alcoholization quality,dispersion degree of similar raw materials and storage capacity utilization rate as evaluation indicators,uses the improved spatial mapping genetic algorithm to optimize the objective function as a whole,and obtains an efficient distribution plan that conforms to the law of storage and logistics of tobacco raw materials.

关 键 词：烟草物流 垛位分配 遗传算法 组合优化 

分 类 号：TS43[农业科学—烟草工业] TP18[自动化与计算机技术—控制理论与控制工程]