This paper aims to introduce a new approach for the design and management of warehousing systems, which involves variable demand patterns in agreement with the life cycle of stock keeping units (SKUs). Two cost-based mixed integer linear programming (MILP) models are formulated to address both the technology selection, e.g. part-to-picker systems (as automated storage and retrieval systems - AS/RS, miniloads, etc.) and picker-to-part order picking systems, and the SKU assignment to the storage areas. In particular, a class based storage assignment over a life cycle picking metric is adopted. This metric is a rolling measure of popularity.The proposed approach, the adopted measure of popularity and the developed models can support (1) decision making for the selection of warehousing and material handling (W&MH) systems, (2) the determination of the storage capacity for the storage classes, (3) the assignment of SKU to the storage classes and (4) the dynamic, i.e., time-based, management of re-warehousing handlings. Two significant numerical examples illustrate the application and the potential of the proposed approach and models. © 2015 Elsevier B.V.
Manzini, R., Accorsi, R., Gamberi, M., Penazzi, S. (2015). Modeling class-based storage assignment over life cycle picking patterns. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 170, 790-800 [10.1016/j.ijpe.2015.06.026].
Modeling class-based storage assignment over life cycle picking patterns
MANZINI, RICCARDO;ACCORSI, RICCARDO;GAMBERI, MAURO;PENAZZI, STEFANO
2015
Abstract
This paper aims to introduce a new approach for the design and management of warehousing systems, which involves variable demand patterns in agreement with the life cycle of stock keeping units (SKUs). Two cost-based mixed integer linear programming (MILP) models are formulated to address both the technology selection, e.g. part-to-picker systems (as automated storage and retrieval systems - AS/RS, miniloads, etc.) and picker-to-part order picking systems, and the SKU assignment to the storage areas. In particular, a class based storage assignment over a life cycle picking metric is adopted. This metric is a rolling measure of popularity.The proposed approach, the adopted measure of popularity and the developed models can support (1) decision making for the selection of warehousing and material handling (W&MH) systems, (2) the determination of the storage capacity for the storage classes, (3) the assignment of SKU to the storage classes and (4) the dynamic, i.e., time-based, management of re-warehousing handlings. Two significant numerical examples illustrate the application and the potential of the proposed approach and models. © 2015 Elsevier B.V.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.