Designing sustainable supply chain networks under uncertain environments: Fuzzy multi-objective programming

Sustainable supply chain networks have attracted considerable attention in recent years as a means of dealing with a broad range of environmental and social issues. This paper reports a multi-objective mathematical programming model for use in the design of a sustainable supply chain network under u...

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Bibliographic Details
Published in:Journal of cleaner production Vol. 174; pp. 1550 - 1565
Main Authors: Tsao, Yu-Chung, Thanh, Vo-Van, Lu, Jye-Chyi, Yu, Vincent
Format: Journal Article
Language:English
Published: Elsevier Ltd 10.02.2018
Subjects:
carbon
Economic benefits
economic costs
emissions
employment opportunities
Environmental and social responsibilities
environmental impact
Fuzzy multi-objective programming
Multi-echelon
social benefit
supply chain
Sustainable supply chain network
Two-phase stochastics programming
uncertainty
Environmental and social responsibilities
Sustainable supply chain network
Economic benefits
Multi-echelon
Two-phase stochastics programming
Fuzzy multi-objective programming
ISSN:0959-6526, 1879-1786
Online Access:Get full text
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Summary:Sustainable supply chain networks have attracted considerable attention in recent years as a means of dealing with a broad range of environmental and social issues. This paper reports a multi-objective mathematical programming model for use in the design of a sustainable supply chain network under uncertain conditions. The proposed model is aimed at maximizing social benefits while minimizing economic costs and environmental impacts. The objective assists in making decisions concerning the selection of production technologies and materials and determining the number and locations of production and distribution centers and the quantity of product to be transported between facilities. Uncertainty related to customer demand is dealt by using stochastic variables, whereas overall costs, carbon emissions, job opportunities, and the detrimental effects of the resulting solutions are handled using fuzzy numbers. An interactive method based on two-phase stochastic programming and fuzzy probabilistic multi-objective programing is used to overcome problems related to uncertainty. Finally, numerical analysis demonstrates the efficacy and efficiency of the proposed model.
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ISSN:0959-6526
1879-1786
DOI:10.1016/j.jclepro.2017.10.272