Optimization of ship-pack in a two-echelon distribution system

The traditional Economic Order Quantity (EOQ) model ignores the physical limitations of distribution practices. Very often distribution centers (DC) have to deliver merchandise in manufacturer-specified packages, which can impose restrictions on the application of the economic order quantity. These manufacturer-specified packages, or ship-packs, include cases (e.g., cartons containing 24 or 48 units), inners (packages of 6 or 8 units) and eaches (individual units). For each Stock Keeping Unit (SKU), a retailer decides which of these ship-pack options to use when replenishing its retail stores. Working with a major US retailer, we have developed a cost model to help determine the optimum warehouse ship-pack. Besides recommending the most economical ship-pack, the model is also capable of identifying candidates for warehouse dual-slotting, i.e., two picking modules for the same SKU that carry two different pack sizes. We find that SKUs whose sales volumes vary greatly over time will benefit more from dual-slotting. Finally, we extend our model to investigate the ideal case configuration for a particular SKU, that is, the ideal size for an inner package.

Department dc:contributor.department

Massachusetts Institute of Technology. Computation for Design and Optimization Program.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Wen, Naijun

Advisor dc:contributor.advisor

• Stephen C. Graves.

• Computation for Design and Optimization Program.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/61903

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/61903