Dynamic supplier selection and lot-sizing problem considering carbon emissions in a big data environment
Kuldeep Lamba and
Surya Prakash Singh
Technological Forecasting and Social Change, 2019, vol. 144, issue C, 573-584
Abstract:
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.
Keywords: Supplier selection; Big Data; Carbon emissions; Lot-sizing; Mixed-integer non-linear program (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S004016251731507X
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:144:y:2019:i:c:p:573-584
DOI: 10.1016/j.techfore.2018.03.020
Access Statistics for this article
Technological Forecasting and Social Change is currently edited by Fred Phillips
More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().