Login | Register

Modelling a closed-loop product recovery system with supply uncertainty


Modelling a closed-loop product recovery system with supply uncertainty

Devu, Venkata Sundar Kamal (2005) Modelling a closed-loop product recovery system with supply uncertainty. Masters thesis, Concordia University.

Text (application/pdf)
MR14304.pdf - Accepted Version


Logistic networks for product recovery have to be implemented in an efficient manner to recover cost savings from remanufacturing. Uncertainty of the quantity and timing of product returns is a major issue in the product recovery networks. Product recovery networks require investments of high fixed costs. Hence the uncertain information has to be taken into account when the strategic network model is designed. This thesis is aimed at presenting a mathematical model for closed-loop product recovery system with uncertainty of product returns. A generic mixed integer-programming model is developed. Stochastic programming approach is implemented in the deterministic model by adding scenarios and probabilities to explicitly account for the uncertainties in the product returns. The model is programmed and solved by LINGO optimization solver. Several test problems are solved by varying the parameters: number of scenarios, probability and return rates to identify the sensitivity of the model. A statistical analysis is conducted on all the example problems by measuring the Expected Value of Perfect Information (EVPI), Value of Stochastic Solution (VSS) and the results are discussed.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical and Industrial Engineering
Item Type:Thesis (Masters)
Authors:Devu, Venkata Sundar Kamal
Pagination:xi, 124 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Mechanical and Industrial Engineering
Thesis Supervisor(s):Chen, Ming Yuan
ID Code:8836
Deposited By: Concordia University Library
Deposited On:18 Aug 2011 18:37
Last Modified:18 Jan 2018 17:34
Related URLs:
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Back to top Back to top