Note. Optimal Storage Assignment Policies for Automated Storage and Retrieval Systems with Stochastic Demands

Ulrich W. Thonemann and Margaret L. Brandeau
Additional contact information
Ulrich W. Thonemann: Department of Industrial Engineering and Engineering Management, Stanford University, Stanford, California 94305-4024
Margaret L. Brandeau: Department of Industrial Engineering and Engineering Management, Stanford University, Stanford, California 94305-4024

Management Science, 1998, vol. 44, issue 1, 142-148

Abstract: In existing AS/RS research, storage assignment policies are evaluated based on the probability that item type j will be stored (and subsequently retrieved). This note applies the turnover-based and class-based assignment policies of Hausman et al. (1976) to a stochastic environment by identifying the kth pallet of item type j: Frequently demanded pallets are stored close to the input/output point and rarely demanded pallets are stored at the end of the storage rack. We consider a discrete storage rack and a continuous storage rack. For the continuous rack case, we develop an expression for expected one-way travel time given uniform and exponentially distributed demand. We show that the turnover-based policy applied to the stochastic environment is optimal (it minimizes one-way travel time) and that both the turnover-based and class-based assignment policies applied in the stochastic environment reduce expected storage/retrieval time compared with random assignment. These savings can be directly translated into increased throughput capacity for existing systems and can be used to improve the design of proposed systems.

Keywords: Manufacturing; Automated Systems (search for similar items in EconPapers)
Date: 1998
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.44.1.142 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:44:y:1998:i:1:p:142-148

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().