Multi-objective decision model for green supply chain management

Article


Chanchaichujit, J., Balasubramanian, S., Shukla, V. and Rosas, J. 2020. Multi-objective decision model for green supply chain management. Cogent Business & Management. 7 (1), pp. 1-33. https://doi.org/10.1080/23311975.2020.1783177
TypeArticle
TitleMulti-objective decision model for green supply chain management
AuthorsChanchaichujit, J., Balasubramanian, S., Shukla, V. and Rosas, J.
Abstract

In this paper, a multi-objective linear programming model was developed which sought to simultaneously optimize total costs and total GHG emissions for the Thai Rubber supply chain. The model was solved by the ε -constraint method which computed the Pareto optimal solution. Each point in the Pareto set entailed a different design of quantity of rubber product flow between the supply chain entities and transport modes and routes. The result obtained show the trade-offs between costs and GHG emissions. It appears that improvements in cost reductions are only possible by compromising on and allowing for higher GHG emissions. From the Pareto set of solutions, each point is equally effective solution for achieving significant cost reductions without compromising too far on GHG emissions. Scenarios analysis were considered to examine the impact of transportation and distribution restructuring on the trade-off between GHG emissions and costs vis-à-vis the baseline model. Overall, the model developed in this research, together with its Pareto optimal solutions analysis, shows that it can be used as an effective tool to design a new and workable GSCM model for the Thai Rubber industry.

LanguageEnglish
PublisherCogent OA, part of Taylor & Francis Group.
JournalCogent Business & Management
ISSN2331-1975
Publication dates
Online29 Jun 2020
Print01 Jan 2020
Publication process dates
Deposited08 Jul 2020
Submitted11 May 2020
Accepted10 Jun 2020
Output statusPublished
Publisher's version
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Copyright Statement

© 2020 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

Digital Object Identifier (DOI)https://doi.org/10.1080/23311975.2020.1783177
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