首页|面向智能制造车间的物料拣选"订单分批-路径规划"两阶段联合调度方法

面向智能制造车间的物料拣选"订单分批-路径规划"两阶段联合调度方法

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"智改数转"背景下,物料拣选效率优化能够极大提升智能制造车间的生产效率,进而推动制造企业智能化水平持续发展.聚焦智能制造车间的物料拣选调度问题,提出了一种面向智能制造车间的物料拣选"订单分批-路径规划"两阶段联合调度方法.首先,基于双商品网络流模型原理,构建"订单分批-路径规划"两阶段联合调度模型.其次,通过定义订单之间的豪斯多夫距离(Hausdroff distance,HD),设计一种嵌入HD邻域搜索策略的遗传算法(NSGA-HD)进行求解.最后,通过不同规模算例仿真,验证了所构建模型和算法的有效性.研究结果表明,所提出的方法能够为智能制造车间物料拣选效率的提升提供决策支持.
A Two-stage Integrated Order Batching and Routing Method for Order Picking in Intelligent Manufacturing
In intelligent manufacturing,efficient order picking can significantly improve productivity in the workshop.A two-stage integrated order batching and routing method was designed for the picking warehouse in intelligent manufacturing.Firstly,according to the order picking process,a two-stage integrated order batching and routing model was constructed based on the two-commodity network flow formulation.Secondly,three neighborhood search strategies based on Hausdroff distance were designed,and then a genetic algorithm with these neighborhood search strategies(NSGA-HD)was proposed.Finally,different sizes of instances were designed to verify the effectiveness of the proposed model and algorithm.The results show that the method has a promising performance and provides decision support for the picking warehouse in intelligent manufacturing.

picking warehouseorder batching and routingtwo-commodity network flow formulationneighborhood searchgenetic algorithm

刁存艺、谢乃明、王玉全

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南京航空航天大学经济与管理学院,江苏南京 211106

车间物料拣选 订单分批与路径规划 双商品网络流模型 邻域搜索 遗传算法

国家自然科学基金资助项目国家自然科学基金资助项目南京航空航天大学中央高校基本科研业务费

7217111692367301NK2023001

2024

工业工程与管理
上海交通大学

工业工程与管理

CSTPCD北大核心
影响因子:0.763
ISSN:1007-5429
年,卷(期):2024.29(4)
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