摘要
目的 采用直发包装SKU归并优化方法,通过减少最小存货单位(Stock Keeping Unit,SKU)的种类,来达到节省物料成本的目的。方法 综合运用k-means聚类分析和组合优化理论,建立直发包装SKU归并模型,并设计基于非均匀变异算子的遗传算法求解方法。以随机生成SKU尺寸信息及其对应的直发包装订购数量的测试数据集为例,通过对比归并前后的SKU种类数和物料成本来验证优化方法的有效性和可行性。结果 优化后,直发包装SKU归并方案中SKU种类的平均降低率为33.13%,归并可使物料成本平均下降2.84%。结论 研究成果可丰富直发包装领域的相关研究,对优化供应链结构,促进包装系列化、智能化发展具有指导意义。
The work aims to use the SKU merging optimization method of delivered with original package(DWOP)to achieve the purpose of saving material costs by reducing the types of stock keeping units(SKUs).K-means clustering analysis and combinatorial optimization theory were used comprehensively to establish the SKU merging model of DWOP.Afterwards,the genetic algorithm based on non-uniform mutation operator was designed to solve this problem.With the test data set of randomly generated SKU size information and its corresponding order quantity of DWOP as an example,the effectiveness and feasibility of the optimization method were verified by comparing the number of SKU types and the material cost of DWOP before and after merging.The results showed that the average reduction rate of the SKU types in the DWOP SKU merging scheme after optimization was 33.13%,and the average material cost reduction rate was 2.84%.The research results can enrich the related research in the field of DWOP and have guiding significance for optimizing the supply chain structure and promoting the serialization and intelligent development of packaging.
作者
徐畅
王军
潘嘹
XU Chang;WANG Jun;PAN Liao(School of Mechanical Engineering,Jiangnan University,Jiangsu Wuxi 214122,China;Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology,Jiangsu Wuxi 214122,China)
出处
《包装工程》
CAS
北大核心
2023年第19期248-257,共10页
Packaging Engineering
基金
国家自然科学基金(51205167)
江苏省自然科学基金(BK20151128)
国家一流学科建设轻工技术与工程(LITE 2018-29)。
关键词
最小存货单位
直发包装
聚类分析
非均匀变异算子
遗传算法
stock keeping unit
delivered with original package
clustering analysis
non-uniform mutation operator
genetic algorithm
