Organizational Unit:

H. Milton Stewart School of Industrial and Systems Engineering

Permanent Link

https://hdl.handle.net/1853/70758

Parent Organization

Organizational Unit

College of Engineering

Includes Organization(s)

Organizational Unit

William M. Keck Virtual Factory Lab (VFL)

ArchiveSpace Name Record

https://finding-aids.library.gatech.edu/agents/corporate_entities/1032

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Publication Search Results

Now showing 1 - 10 of 35

Material transport system design in manufacturing

(Georgia Institute of Technology, 2006-04-06) Wan, Yen-Tai

This dissertation focuses on the material transport system design problem (MTSDP), integrating decisions of technology selection and flow network design. This research is motivated by the design of material transport systems (MTS) in manufacturing plants. The objective is to design a MTS with minimum lifetime costs, subject to service requirements, flow network restrictions, and limited resources. We characterize the MTSDP from the perspectives of task requirements, transport technology, and space utilization. A classification is proposed for transport technologies such that instances in the same class share the same properties, and a decision framework is proposed to emphasize the inter-relationships of three major decisions: task clustering, network connecting, and technology selection. We consider fixed and variable costs, arc capacities, and empty travel in our formulations. We propose two solution approaches for the MTSDP. The first is the compact formulation (CF) approach where the three major decisions are handled by a mixed integer non-linear programming (MINLP) formulation. Relaxation techniques are applied to linearize the model. The solution of the resulting linear formulation (MILP) provides a lower bound to that of MINLP. A tightened formulation reduces the computational time by a factor of 3.85. The experiment also shows that when control system costs are significant, designs with multiple-task clusters are more economical than those restricted to single-task clusters. The other approach is clustering/set partition (CSP), where the three decisions are decomposed and solved sequentially. In an example MTS design problem, three methods are compared: CSP, a GREEDY approach from the literature, and enumeration. CSP finds the optimal solution, while GREEDY results in 31% greater costs. A similar comparison with another example is made for the CF and CSP approaches. We apply the CSP approach in a case problem, using data from an auto parts manufacturer. We include flow path crossing constraints and perform experiments to determine solution quality over a range of small problem sizes. The largest difference from optimality is 3.34%, and the average is 0.98%. More importantly, based on these experiments, it seems there is no evidence that the difference percentage grows with an increase in the number of tasks.
Minimizing Multi-zone Orders in the Correlated Storage Assignment Problem

(Georgia Institute of Technology, 2005-01-14) Garfinkel, Maurice

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%.
Multi-Tier Inventory Systems With Space Constraints

(Georgia Institute of Technology, 2004-04-12) Jernigan, Stephanie A.

In the warehouse of a large cosmetics company, a mechanized order picker is restocked from nearby shelving, and the shelving is restocked from bulk storage, forming a three-tier inventory system. We consider such multi-tier inventory systems and determine the storage areas to which to assign items, and the quantities in which to store them, in order to minimize the total cost of picking items and restocking storage locations. With this research, we increase the number of inventory systems for which simple search algorithms find a provably near-optimal solution. The model and method were tested on data from the Avon Products distribution center outside Atlanta; the solution identified by the model reduced picking and restocking costs there by 20%. The sales forecasts of items stored in the warehouse may change, however, and new items will be introduced into the inventory system and others removed. To account for these changes, some warehouses may periodically reassign items to storage areas and recompute their storage quantities. These reassignment activities account for additional costs in the warehouse. The second focus of this research examines these costs over several time periods in a simple multi-tier inventory system. We develop heuristics to determine the storage areas to which to assign items and the quantities in which to store them in each time period, in order to minimize the total cost of picking items, restocking storage locations, and reassigning skus over multiple periods.
Executive compensation : performance for pay

(Georgia Institute of Technology, 2001-12) Guzzetta, Judith T.
Modeling considerations in data envelopment analysis

(Georgia Institute of Technology, 1995-08) Anderson, Timothy R. (Timothy Roy)
An integrated framework for plant layout evaluation

(Georgia Institute of Technology, 1995-05) Lin, Lie-Chien
Goal oriented multiple criteria decision making for public works capital investment problems involving infrastructure with a specific case study of the US Army

(Georgia Institute of Technology, 1995-05) Lind, Elizabeth Anne
Economic evaluation and justification of industrial automation

(Georgia Institute of Technology, 1993-05) Owen, John J., IIII
Evaluation and recommendation of storage space forecasting model(s)

(Georgia Institute of Technology, 1992-08) McCarty, Laura Smith
A structured procedure for order pick system analysis and design

(Georgia Institute of Technology, 1991-12) Yoon, Chang S.