Title:
Minimizing Multi-zone Orders in the Correlated Storage Assignment Problem

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dc.contributor.advisor Sharp, Gunter P.
dc.contributor.advisor Sokol, Joel S.
dc.contributor.author Garfinkel, Maurice en_US
dc.contributor.committeeMember Barnes, Earl R.
dc.contributor.committeeMember Navathe, Shamkant
dc.contributor.committeeMember Vande Vate, John
dc.contributor.department Industrial and Systems Engineering en_US
dc.date.accessioned 2005-07-28T17:51:08Z
dc.date.available 2005-07-28T17:51:08Z
dc.date.issued 2005-01-14 en_US
dc.description.abstract A fundamental issue in warehouse operations is the storage location of the products it contains. Placing products intelligently within the system can allow for great reductions in order pick costs. This is essential because order picking is a major cost of warehouse operations. For example, a study by Drury conducted in the UK found that 63% of warehouse operating costs are due to order picking. When orders contain a single item, the COI rule of Heskett is an optimal storage policy. This is not true when orders contain multiple line items because no information is used about what products are ordered together. In this situation, products that are frequently ordered together should be stored together. This is the basis of the correlated storage assignment problem. Several previous researchers have considered how to form such clusters of products with an ultimate objective of minimizing travel time. In this dissertation, we focus on the alternate objective of minimizing multi-zone orders. We present a mathematical model and discuss properties of the problem. A Lagrangian relaxation solution approach is discussed. In addition, we both develop and adapt several heuristics from the literature to give upper bounds for the model. A cyclic exchange improvement method is also developed. This exponential size neighborhood can be efficiently searched in polynomial time. Even for poor initial solutions, this method finds solutions which outperform the best approaches from the literature. Different product sizes, stock splitting, and rewarehousing are problem features that our model can handle. The cyclic exchange algorithm is also modified to allow these operating modes. In particular, stock splitting is a difficult issue which most previous research in correlated storage ignores. All of our algorithms are implemented and tested on data from a functioning warehouse. For all data sets, the cyclic exchange algorithm outperforms COI, the standard industry approach, by an average of 15%. en_US
dc.description.degree Ph.D. en_US
dc.format.extent 1040618 bytes
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/6837
dc.language.iso en_US
dc.publisher Georgia Institute of Technology en_US
dc.subject Warehousing
dc.subject Storage assignment
dc.subject Correlated storage
dc.subject Improvement heuristics
dc.subject Cyclic exchange
dc.subject Lagrangian relaxation en_US
dc.title Minimizing Multi-zone Orders in the Correlated Storage Assignment Problem en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Sharp, Gunter P.
local.contributor.advisor Sokol, Joel S.
local.contributor.corporatename H. Milton Stewart School of Industrial and Systems Engineering
local.contributor.corporatename College of Engineering
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