Article ID Journal Published Year Pages File Type
4972518 Decision Support Systems 2017 14 Pages PDF
Abstract

•The proposed system tracks both inventory items and mobile warehouse equipment at the item level.•A flexible warehouse scenario where items are dropped and picked as per convenience.•Flexible configuration by relaxing both location constraint and local capacity constraints with a periodically renewable global capacity.•The proposed flexible storage system performs better than static systems.

We propose a smart warehouse environment where not only inventory items but also the shelves are tracked by an RFID-based system. Both operational activities and warehouse configurations are continually monitored to facilitate real-time response. We study the dynamics of a flexible warehouse scenario where items of any type can be dropped off anywhere within the premises. Unlike existing models, we relax both the location constraint and local (e.g., item-type level) capacity constraints with a periodically renewable fixed global capacity. Dynamic decisions on location and local capacity are made based on the stochastic Markovian demand states. We optimize processing and routing constraints and compare the performance of this flexible storage setup with classical models through multiple levels of real-time decision support. Our results provide corroborating evidence to support the following observations: (1) “free pick-n-drop” combined with fluid warehousing mechanism greatly reduces trip costs and lead time for single trip demand, (2) there exists a lower bound on the performance in such a setup with fixed local capacities, and (3) the lower bound can be further improved when inventory capacity and location are dynamically adjusted according to actual demand patterns.

Related Topics
Physical Sciences and Engineering Computer Science Information Systems
Authors
, , , ,