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Stock location assignment and order ...

Frazelle, Edward Hardy.

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Stock location assignment and order picking productivity.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Stock location assignment and order picking productivity./
作者:	Frazelle, Edward Hardy.
面頁冊數:	159 p.
附註:	Source: Dissertation Abstracts International, Volume: 52-02, Section: B, page: 1002.
Contained By:	Dissertation Abstracts International52-02B.
標題:	Engineering, Industrial. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9120762

Stock location assignment and order picking productivity.
Frazelle, Edward Hardy.

Stock location assignment and order picking productivity. - 159 p.

Source: Dissertation Abstracts International, Volume: 52-02, Section: B, page: 1002.

Thesis (Ph.D.)--Georgia Institute of Technology, 1989.

Given a set of items and associated space requirements, a warehouse layout, and an order batching and pick sequencing policy, the stock location assignment problem (SLAP) is the problem to determine an assignment of items to locations in a warehouse that minimizes total order picking time. Since the majority of operating costs in a typical warehouse can be attributed to order picking, good solutions to the SLAP can significantly reduce total order picking time. Improvements stem from reductions in the number of location visits required to pick an order and reductions in the travel between location visits. The problem is intellectually motivated by its complexity, the size of practical manifestations of the problem, and the lack of prior research in the area.Subjects--Topical Terms:

626639
Engineering, Industrial.

Stock location assignment and order picking productivity.
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245 1 0 $a Stock location assignment and order picking productivity.
300 $a 159 p.
500 $a Source: Dissertation Abstracts International, Volume: 52-02, Section: B, page: 1002.
500 $a Directors: G. P. Sharp; J. A. White.
502 $a Thesis (Ph.D.)--Georgia Institute of Technology, 1989.
520 $a Given a set of items and associated space requirements, a warehouse layout, and an order batching and pick sequencing policy, the stock location assignment problem (SLAP) is the problem to determine an assignment of items to locations in a warehouse that minimizes total order picking time. Since the majority of operating costs in a typical warehouse can be attributed to order picking, good solutions to the SLAP can significantly reduce total order picking time. Improvements stem from reductions in the number of location visits required to pick an order and reductions in the travel between location visits. The problem is intellectually motivated by its complexity, the size of practical manifestations of the problem, and the lack of prior research in the area.
520 $a The SLAP was formulated as an integer programming problem. The number of location visits required to pick an order and the distance between those location visits was shown to be a primary determiner of total order picking time. A general objective function formulation with accompanying packing, congestion, and assignment constraints revealed the problem to be a unary NP-hard problem. The complexity and size of practical manifestations of the SLAP motivated our decision to pursue a heuristic as opposed to an exact solution approach. Based on insight and intuition developed in previous attempts to solve the SLAP and documented in a small example, a two-phase construction heuristic was developed. The heuristic is based on clustering items that are likely to appear together on an order and assigning clusters to warehouse locations based on their adjusted popularity. The heuristic makes use of a statistical analysis of a sample of order data and a graphical representation of the statistical analysis. The heuristic was evaluated in case studies of end-of-aisle and in-the-aisle order picking systems. Analytical expressions for end-of-aisle picking productivity as a function of the travel speed of the storage/retrieval device, system length and height, the distribution of bin processing times, and the skew of the activity distribution were derived to help separate the effects of popularity storage, correlated assignments, and order batching. Similarly, analytical expressions for in-the-aisle picking systems were derived to help separate the same effects. In both end-of-aisle and in-the-aisle systems, the procedure is shown to yield 20% to 50% reductions in total order picking time.
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790 1 0 $a White, J. A., $e advisor
790 $a 0078
791 $a Ph.D.
792 $a 1989
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