Development of environmentally sustainable supply chain networks

Download files
Access & Terms of Use
open access
Copyright: Boonsothonsatit, Kanda
Altmetric
Abstract
The development of a generic Decision Support System (DSS) for Supply Chain Network Design (SCND) is one of the most challenging research areas in Supply Chain Management. It must evolve with an emphasis on improving the supply chain performances; to reduce the cost, lead time and environmental impact. The three performances are generally influenced by several planning decisions (i.e. sources of supply and facility locations, order quantity allocations, transportation modes and lot-sizes) and various time-dependent parameters (e.g. currency exchange rates). As a result, there is a need to develop a generic decision support system to assist in designing the supply chain network by considering the issues aforementioned. This research aims to develop a generic DSS for an environmentally sustainable SCND. It covers from cradle-to-gate stages that aim to achieve the lowest cost, shortest lead time and least environmental impact in a dynamic environment. The development of a generic DSS applies the integration of Fuzzy Goal Programming (FGP) with a weighted max-min operator and system dynamics optimisation with Powell algorithm. The FGP with a weighted max-min operator is used to trade-off the multiple conflicting objectives and overcome vagueness in target values of the individual objectives. The multivariable and dynamic behaviour is configured and solved by using the system dynamics optimisation with Powell algorithm. The generic DSS eventually suggests the best-fitted sources of supply and facility locations, the optimal order quantity allocations, and the appropriate transportation modes and lot-sizes in order to achieve the aim of this research.
Persistent link to this record
Link to Publisher Version
Link to Open Access Version
Additional Link
Author(s)
Boonsothonsatit, Kanda
Supervisor(s)
Kara, Sami
Creator(s)
Editor(s)
Translator(s)
Curator(s)
Designer(s)
Arranger(s)
Composer(s)
Recordist(s)
Conference Proceedings Editor(s)
Other Contributor(s)
Corporate/Industry Contributor(s)
Publication Year
2014
Resource Type
Thesis
Degree Type
PhD Doctorate
UNSW Faculty
Files
download public version.pdf 2.54 MB Adobe Portable Document Format
Related dataset(s)