Dynamic supplier selection and lot-sizing problem considering carbon emissions in a big data environment

Selection of the right suppliers with a view of overall reduction in the procurement cost as well as carbon emissions is an important task for the buyers to sustain in the fierce competitive environment The rising concerns about carbon emissions due to severe climatic changes globally have forced supply chain managers to restrategize about controlling their carbon emissions. This paper proposes a dynamic supplier selection model incorporating the carbon emissions under the carbon cap-and-trade scenario. Carbon emissions caused due to ordering, holding the inventory, production and handling and transportation have been considered in the paper. The proposed mathematical model is a mixed-integer-non-linear-program (MINLP). Validation of the proposed MINLP has been done using two randomly generated datasets having the essential parameters of Big Data, i.e. volume, velocity, and variety.