4.1 Article

AMR-Assisted Order Picking: Models for Picker-to-Parts Systems in a Two-Blocks Warehouse

期刊

ALGORITHMS
卷 15, 期 11, 页码 -

出版社

MDPI
DOI: 10.3390/a15110413

关键词

AMR-assisted; hybrid order picking system; picker-to-parts system; mixed integer linear programming; optimization; two-blocks warehouse; case study

向作者/读者索取更多资源

This study focuses on a hybrid picker-to-parts order picking system, where human operators collaborate with Automated Mobile Robots (AMRs), presenting new mathematical models for optimization and synchronization of picking operations experimentally evaluating alternative implementations for the AMR system.
Manual order picking, the process of retrieving stock keeping units from their storage location to fulfil customer orders, is one of the most labour-intensive and costly activity in modern supply chains. To improve the outcome of order picking systems, automated and robotized components are increasingly introduced creating hybrid order picking systems where humans and machines jointly work together. This study focuses on the application of a hybrid picker-to-parts order picking system, in which human operators collaborate with Automated Mobile Robots (AMRs). In this paper a warehouse with a two-blocks layout is investigated. The main contributions are new mathematical models for the optimization of picking operations and synchronizations. Two alternative implementations for an AMR system are considered. In the first one handover locations, where pickers load AMRs are shared between pairs of opposite sub-aisles, while in the second they are not. It is shown that solving the mathematical models proposed by the meaning of black-box solvers provides a viable algorithmic optimization approach that can be used in practice to derive efficient operational plannings. The experimental study presented, based on a real warehouse and real orders, finally allows to evaluate and strategically compare the two alternative implementations considered for the AMR system.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.1
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据