An optimization model for green supply chain management by using a big data analytic approach

Abstract This paper presents a multi-objective optimization model for a green supply chain management scheme that minimizes the inherent risk occurred by hazardous materials, associated carbon emission and economic cost. The model related parameters are capitalized on a big data analysis. Three scenarios are proposed to improve green supply chain management. The first scenario divides optimization into three options: the first involves minimizing risk and then dealing with carbon emissions (and thus economic cost); the second minimizes both risk and carbon emissions first, with the ultimate goal of minimizing overall cost; and the third option attempts to minimize risk, carbon emissions, and economic cost simultaneously. This paper provides a case study to verify the optimization model. Finally, the limitations of this research and approach are discussed to lay a foundation for further improvement.