摘要
物流配送中心中,减小订单拣选行走距离进而优化人工拣选作业系统可有效提高客户满意度,降低成本.货位指派和拣选方式是影响拣选行走距离的两个重要因素.作者在分类存储的货位指派策略下、分别对返回型和S型拣选方式,建立了拣选距离随机模型.仿真结果表明,模型结果能在误差允许条件下较好地与仿真逼近.通过在4种物品订购频率和货位分配情况下对返回型和S型拣选方式的比较,得出两种拣选方式各自适用的情况.
Reducing order picking travel distance and then optimizing manual order picking system can improve customer satisfaction degree effectively and reduce costs largely in logistics distribution center. Storage assignment strategy and picker route are two essential factors influencing picking distance. Under the circumstance of sorted-storage return-type and S-type picking, picking route stochastic models for logistics distribution center manual order picking are built. Simulation results show that model can approximate simulation well under the condition of permission difference. Contrasting model approximation calculation results of return-type and S-type picking route under four goods ordered frequencies and storage assign- ment, the best aoDlication cases of two picking method are obtained.
出处
《系统科学与数学》
CSCD
北大核心
2011年第8期921-931,共11页
Journal of Systems Science and Mathematical Sciences
基金
国家自然科学基金(70971011)
北京市属高等学校人才强教深化计划(PHR201007145)
北京市教委项目(SM201110037004)
关键词
人工拣选
分类存储
随机模型
仿真.
Manual order picking, sorted-storage, stochastic model, simulation.
