Batch Assorting for Worker-following Assortment Carts in Parallel-aisle Order-assorting Systems

Batch Assorting for Worker-following Assortment Carts in Parallel-aisle Order-assorting Systems

Author: Taehoon Lee, Jeongman Lee and Soondo Hong

https://doi.org/10.1109/ACCESS.2022.3169181 [PDF]

• This study introduces an order-assorting system (OAS) in a distribution center which supports assortments with worker-following carts.
• The proposed approaches are two mixed-integer programming models, the batching-only model (BOM) and the binning and batching model (BBM). The authors also propose the route packing-based binning then batching (RPBB) heuristic to solve a large-sized BBM problem consisting of a binning procedure based on route packing (BPM-RP) and a batching procedure using a simple integer programming formulation.
• The paper contributes to formulate a mixed-integer programming (MIP) model for binning and batching operations which minimizes the total travel distance for small-sized problems and propose the route packing-based heuristic to solve a practical situation in large-sized problems with the binning and batching operations in the OAS.
• This paper reveals that BBM minimizes the total travel distance of carts for the OASs that use worker-following cart systems. Furthermore, by proposing BBM and RPBB that shorten the total travel distance by optimizing the balance between binning and batching, this result indicates that RPBB obtains near-optimal solutions by the tight lower bound and can solve large-sized problem.