An optimization model for strategic supply chain design under stochastic capacity disruptions /

Bibliographic Details
Main Author: Luna Coronado, Jaime, 1974-
Other Authors: Gaukler, Gary M. (Thesis advisor), Arreola Risa, Antonio (Thesis advisor)
Format: Thesis eBook
Language:English
Published: [College Station, Tex.] : [Texas A&M University], [2008]
Subjects:
Online Access:Link to OAK Trust copy
Description
Abstract:This Record of Study contains the details of an optimization model developed for Shell Oil Co. This model will be used during the strategic design process of a supply chain for a new technology commercialization. Unlike traditional supply chain deterministic optimization, this model incorporates different levels of uncertainty at suppliers' nominal capacity. Because of the presence of uncertainty at the supply stage, the objective of this model is to define the best diversification and safety stock level allocated to each supplier, which minimize the total expected supply chain cost. We propose a Monte Carlo approach for scenario generation, a two-stage non-linear formulation and the Sample Average Approximation (SAA) procedure to solve the problem near optimality. We also propose a simple heuristic procedure to avoid the nonlinearity issue. The sampling and heuristic optimization procedures were implemented in a spreadsheet with a user's interface. The main result of this development is the analysis of the impact of diversification in strategic sourcing decisions, in the presence of stochastic supply disruptions.
Item Description:"Major Subject: Engineering"
Title from author supplied metadata (automated record created on Oct. 13, 2008.)
Vita.
Abstract.
Electronic resource.
Format:Mode of access: World Wide Web.
System requirements: World Wide Web access and Adobe Acrobat Reader.
Bibliography:Includes bibliographical references.