Multi-objective decision model for green supply chain management

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...

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Autores principales:	Janya Chanchaichujit, Sreejith Balasubramanian, Vinaya Shukla, Jose-Saavedra Rosas
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2020
Materias:	green supply chain management multi-objective optimization rubber industry ghg emissions Business HF5001-6182 Management. Industrial management HD28-70
Acceso en línea:	https://doaj.org/article/a146dd3904464ea688b2a1d4b10c4180
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spelling	oai:doaj.org-article:a146dd3904464ea688b2a1d4b10c41802021-12-02T17:00:22ZMulti-objective decision model for green supply chain management2331-197510.1080/23311975.2020.1783177https://doaj.org/article/a146dd3904464ea688b2a1d4b10c41802020-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311975.2020.1783177https://doaj.org/toc/2331-1975In 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.Janya ChanchaichujitSreejith BalasubramanianVinaya ShuklaJose-Saavedra RosasTaylor & Francis Grouparticlegreen supply chain managementmulti-objective optimizationrubber industryghg emissionsBusinessHF5001-6182Management. Industrial managementHD28-70ENCogent Business & Management, Vol 7, Iss 1 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	green supply chain management multi-objective optimization rubber industry ghg emissions Business HF5001-6182 Management. Industrial management HD28-70
spellingShingle	green supply chain management multi-objective optimization rubber industry ghg emissions Business HF5001-6182 Management. Industrial management HD28-70 Janya Chanchaichujit Sreejith Balasubramanian Vinaya Shukla Jose-Saavedra Rosas Multi-objective decision model for green supply chain management
description	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.
format	article
author	Janya Chanchaichujit Sreejith Balasubramanian Vinaya Shukla Jose-Saavedra Rosas
author_facet	Janya Chanchaichujit Sreejith Balasubramanian Vinaya Shukla Jose-Saavedra Rosas
author_sort	Janya Chanchaichujit
title	Multi-objective decision model for green supply chain management
title_short	Multi-objective decision model for green supply chain management
title_full	Multi-objective decision model for green supply chain management
title_fullStr	Multi-objective decision model for green supply chain management
title_full_unstemmed	Multi-objective decision model for green supply chain management
title_sort	multi-objective decision model for green supply chain management
publisher	Taylor & Francis Group
publishDate	2020
url	https://doaj.org/article/a146dd3904464ea688b2a1d4b10c4180
work_keys_str_mv	AT janyachanchaichujit multiobjectivedecisionmodelforgreensupplychainmanagement AT sreejithbalasubramanian multiobjectivedecisionmodelforgreensupplychainmanagement AT vinayashukla multiobjectivedecisionmodelforgreensupplychainmanagement AT josesaavedrarosas multiobjectivedecisionmodelforgreensupplychainmanagement
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Multi-objective decision model for green supply chain management

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