李丽,刘保国,武照云,何学武,赵彬彬.基于改进人工蜂群算法的四向穿梭车仓储系统货位优化研究[J].包装工程,2024,45(19):265-274.
LI Li,LIU Baoguo,WU Zhaoyun,HE Xuewu,ZHAO Binbin.Optimization of Storage Allocation Based on Improved Artificial Bee Colony Algorithm in Four-way-shuttle Based Storage and Retrieval System[J].Packaging Engineering,2024,45(19):265-274. |
| 基于改进人工蜂群算法的四向穿梭车仓储系统货位优化研究 |
| Optimization of Storage Allocation Based on Improved Artificial Bee Colony Algorithm in Four-way-shuttle Based Storage and Retrieval System |
| 投稿时间：2024-05-23 |
| DOI：10.19554/j.cnki.1001-3563.2024.19.026 |
| 中文关键词: 四向穿梭车 仓储系统 货位分配 人工蜂群算法 |
| 英文关键词:four-way-shuttle storage and retrieval system storage allocation artificial bee colony algorithm |
| 基金项目:国家自然科学基金(12072106);河南省科技攻关项目(222103810085，232103810085，242102220029) |
| 作者 | 单位 |
| 李丽 | 河南工业大学 机电工程学院，郑州 450001 |
| 刘保国 | 河南工业大学 机电工程学院，郑州 450001 |
| 武照云 | 河南工业大学 机电工程学院，郑州 450001 |
| 何学武 | 河南工业大学 机电工程学院，郑州 450001 |
| 赵彬彬 | 河南工业大学 机电工程学院，郑州 450001 |
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| Author | Institution |
| LI Li | School of Mechanical & Electrical Engineering, Henan University of Technology, Zhengzhou 450001, China |
| LIU Baoguo | School of Mechanical & Electrical Engineering, Henan University of Technology, Zhengzhou 450001, China |
| WU Zhaoyun | School of Mechanical & Electrical Engineering, Henan University of Technology, Zhengzhou 450001, China |
| HE Xuewu | School of Mechanical & Electrical Engineering, Henan University of Technology, Zhengzhou 450001, China |
| ZHAO Binbin | School of Mechanical & Electrical Engineering, Henan University of Technology, Zhengzhou 450001, China |
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| 中文摘要: |
| 目的 针对四向穿梭车仓储系统中多设备并行作业的特点和高效作业的需求，对其货位优化进行研究。方法 建立了考虑入库效率、货架稳定性、作业均衡度和货物关联性4个因素的货位分配组合优化模型，设计了改进人工蜂群算法求解该模型。利用多目标Pareto支配解概念生成初始解，融合遗传算法和变邻域搜索算法思想进行解的优化搜索，以提高算法的性能。为更好地确定算法参数，进行了算法参数敏感性试验。针对3种(大、中、小)入库规模和9种不同仓位下的入库，进行了改进人工蜂群算法、遗传算法和蚁群算法3种算法的求解。结果 入库规模越大，改进人工蜂群算法优势越明显，大规模下相比遗传算法和蚁群算法，其性能分别提升了13.14%和19.32%;不同仓位下相比另2种算法，其性能提升了6.38%~26.76%。结论 文中所建立的货位分配优化模型更接近仓储系统的实际工作状态，所提出的算法能够有效进行入库货位分配，提高了仓库运作效率。 |
| 英文摘要: |
| Aiming at the characteristics of multi-equipment parallel operation and the requirement of high-efficiency operation in four-way-shuttle based storage and retrieval systems, the work aims to study the optimization of storage allocation. A combined optimization model of storage allocation was established, which took into account the factors of storage efficiency, shelf stability, work balance and goods correlation, and then an improved artificial bee colony algorithm was designed to solve the model. The concept of multi-objective Pareto dominated solution was used to generate the initial solution, and the thought of genetic algorithm and variable neighborhood search algorithm were combined to optimize the solution, which improved the performance of the algorithm. A sensitivity test of algorithm parameters was carried out to determine the parameters. The effectiveness of the proposed algorithm was verified by simulation experiments under three different storage scales (large, medium and small) and nine goods stored scales. The solution of three algorithms (the improved artificial bee colony algorithm, the genetic algorithm, and the ant colony algorithm) signified that the larger the storage scale was, the more obvious the superiority of the improved artificial bee colony algorithm was. Compared with the genetic algorithm and the ant colony algorithm, the performance of the improved artificial bee colony algorithm under largestorage scale was improved by 13.14% and 19.32%, respectively, and its performance under differentgoods stored scales was improved by 6.38%-26.76%. In conclusion, the established optimization model is closer to the actual working state of warehouse, and the proposed algorithm can effectively allocate the storage space and improve the efficiency of the warehouse operation. |
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