Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/12986
Title: Distribution network design for reverse logistics operations
Authors: DONG MENG
Keywords: Reverse logistics; Product recovery; Meta-heuristics; Stochastic programming; Sample average approximation; Importance sampling
Issue Date: 24-Nov-2007
Source: DONG MENG (2007-11-24). Distribution network design for reverse logistics operations. ScholarBank@NUS Repository.
Abstract: This thesis focuses on one of the important aspects of the reverse logistics network design, in which the integration of forward and reverse logistics operations is considered. Furthermore, due to its inherent complexity, the efficient solution methods for such problem are also designed.The approach to an integrated distribution network design for electronic products recovery is first investigated in this thesis. In the second part of this thesis, another deterministic mathematical model is developed for heterogeneous products recovery network design. Based on that, a stochastic programming based approach is presented by which the deterministic models for reverse distribution network design can be extended to explicitly account for uncertainties in the third part of this thesis. A solution approach integrating a recently proposed sampling method with an acceleration strategy is also developed. Moreover, the design of sustainable logistics network under uncertainty is also investigated in the fourth part of this research. An important sampling strategy is applied to improve the performance of the sample average approximation method. Finally, a dynamic location and allocation model is developed to cope with multiperiod reverse distribution network design problem.
URI: http://scholarbank.nus.edu.sg/handle/10635/12986
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Phd Dissertation_DongMeng_HT031467N.pdf1.33 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

263
checked on Dec 11, 2017

Download(s)

306
checked on Dec 11, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.