Development of a Generic decision support system based on multi-Objective Optimisation for Green supply chain network design (GOOG)
Journal of Manufacturing Technology Management
ISSN: 1741-038X
Article publication date: 7 September 2015
Abstract
Purpose
The purpose of this paper is to propose a Generic decision support system which is based on multi-Objective Optimisation for Green supply chain network design (GOOG). It aims to support decision makers to design their supply chain networks using three key objectives: the lowest cost and environmental impact and the shortest lead time by incorporating the decision maker’s inputs.
Design/methodology/approach
GOOG aims to suggest the best-fitted parameters for supply chain partners and manufacturing plant locations, their order allocations, and appropriate transportation modes and lot-sizes for cradle-to-gate. It integrates Fuzzy Goal Programming and weighted max-min operator for trade-off conflicting objectives and overcome fuzziness in specifying target values of individual objectives. It is solved using exact algorithm and validated using an industrial case study.
Findings
The comparative analysis between actual, three single-objective, and multi-objective decisions showed that GOOG is capable to optimising three objectives namely cost, lead time, and environmental impact.
Research limitations/implications
Further, GOOG requires validation for different supply chain scenarios and manufacturing strategic decisions. It can improve by including multi-echelon supply chain networks, entire life cycle and relevant environmental legislations.
Practical implications
GOOG helps the decision makers to configuring those supply chain parameters whilst minimising those three objectives.
Social implications
Companies can use GOOG as a tool to strategically select their supply chain that reduces their footprint and stop rebound effect which imposes significant impact to the society.
Originality/value
GOOG includes overlooked in the previous study in order to achieve the objectives set. It is flexible for the decision makers to change the relative weightings of the inputs for those contradicting objectives.
Keywords
Acknowledgements
The authors would be most grateful to all partners in the Sustainable Manufacturing and Life Cycle Engineering Research Group, the School of Mechanical and Manufacturing Engineering, The University of New South Wales for their valuable knowledge and information sharing. In addition, the authors are indebted to the financial contribution of the Royal Thai Government as well as a cryogenic storage tank manufacturing company in Thailand for data provision.
Citation
Boonsothonsatit, K., Kara, S., Ibbotson, S. and Kayis, B. (2015), "Development of a Generic decision support system based on multi-Objective Optimisation for Green supply chain network design (GOOG)", Journal of Manufacturing Technology Management, Vol. 26 No. 7, pp. 1069-1084. https://doi.org/10.1108/JMTM-10-2012-0102
Publisher
:Emerald Group Publishing Limited
Copyright © 2015, Emerald Group Publishing Limited