Title:
Integrated Decisions for Supply Chain Design and Inventory Allocation Problem

Simple item page
dc.contributor.advisor Lu, Jye-Chyi
dc.contributor.advisor Al-Khayyal, Faiz
dc.contributor.author Mangotra, Divya en_US
dc.contributor.committeeMember Zhou, Chen
dc.contributor.committeeMember Ferguson, Mark
dc.contributor.committeeMember Griffin, Paul
dc.contributor.department Industrial and Systems Engineering en_US
dc.date.accessioned 2008-02-07T18:41:58Z
dc.date.available 2008-02-07T18:41:58Z
dc.date.issued 2007-11-12 en_US
dc.description.abstract Manufacturing outsourcing in the U.S. has never been stronger than it is today. Increased outsourcing has led to significant changes in the design of the retail distribution network. While the traditional distribution network had the manufacturing plants supplying goods to the retail stores directly, the off-shore manufacturing has increased the network's demand for transportation and warehousing to deliver the goods. Thus, most companies have a complex distribution network with several import and regional distribution centers (RDC). In this thesis, we study an integrated facility location and inventory allocation problem for designing a distribution network with multiple national (import) distribution centers (NDC) and retailers. The key decisions are where to locate the RDCs and how much inventory to hold at the different locations such that the total network cost is minimized under a pre-defined operational rule for the distribution of goods. In particular, the inventory cost analysis is based on the continuous review batch ordering policy and the base-stock policy. Both Type-I (probability of stock-outs) and Type-II (fill-rate) service level measures are used in the analysis. Two different models are presented in this thesis for solving the integrated facility location-inventory allocation problem. The first model, continuous approximation (CA), assumes the distribution network to be located in a continuous region and replaces the discrete store locations with a store density function. The second model is a discrete representation of the problem as a mixed integer programming problem. Both the models take a nonlinear form and solution techniques are developed using the theory of nonlinear programming and linear reformulation of nonlinear problems. The goal of the first part of the thesis is to model the problem using a modified CA approach and an iterative solution scheme is presented to solve it. The main contribution of this work lies in developing a refined CA modeling technique when the discrete data cannot be modeled by a continuous function. In addition, the numerical analysis suggests that the total network cost is significantly lower in the case of the integrated model as compared with the non-integrated model. It is also shown that the regular CA approach leads to a solution which is inferior to the solution obtained by the modified CA approach. Our analysis shows that the type of service measure used affects the network design. In the second part of the thesis, the problem is modeled as a nonlinear mixed integer program and a linear reformulation solution technique is proposed to obtain a lower bound on the original problem. Computational results are presented for small problem instances. We conclude this part of the thesis by presenting an integrated model when a base stock inventory policy is used. A drop-decomposition heuristic is proposed to solve this problem. en_US
dc.description.degree Ph.D. en_US
dc.identifier.uri http://hdl.handle.net/1853/19814
dc.publisher Georgia Institute of Technology en_US
dc.subject Continuous approximation en_US
dc.subject Inventory allocation en_US
dc.subject Facility location en_US
dc.subject Nonlinear optimization en_US
dc.subject Continuous review policy en_US
dc.subject.lcsh Nonlinear programming
dc.subject.lcsh Physical distribution of goods
dc.subject.lcsh Warehouses
dc.title Integrated Decisions for Supply Chain Design and Inventory Allocation Problem en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Lu, Jye-Chyi
local.contributor.corporatename H. Milton Stewart School of Industrial and Systems Engineering
local.contributor.corporatename College of Engineering
relation.isAdvisorOfPublication 4370d307-55cb-4bc3-9d5e-640823e16205
relation.isOrgUnitOfPublication 29ad75f0-242d-49a7-9b3d-0ac88893323c
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
mangotra_divya_200712_phd.pdf.pdf
Size:
667.36 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Theses and Dissertations