TY - JOUR
T1 - Effect of carbon tax on reverse logistics network design
AU - Reddy, K Nageswara
AU - Kumar, Akhilesh
AU - Sarkis, Joseph
AU - Tiwari, Manoj Kumar
PY - 2019/11/18
Y1 - 2019/11/18
N2 - Reverse logistics network design (RLND) is getting momentum as more organizations realize the benefits of recycling or remanufacturing of their end-of-life products. Similarly, there is an impetus for organizations to become more environmentally conscious or green. This environmental context has driven many organizations to invest in green technologies, with a recent emphasis on reducing greenhouse gas emissions. This environmental investment situation and decision can be addressed through the integration of facility location, operational planning, and vehicle type selection, while simultaneously accounting for carbon emissions from vehicles, inspection centers, and remanufacturing centers in a reverse logistics (RL) context. In the current study, we present a mixed-integer linear programming (MILP) model to solve a multi-tier multi-period green RL network, including vehicle type selection. This research integrates facility locations, vehicle type selection with emissions producing from transportation and operations at various processing centers. Prior research does not account for carbon emissions for this design problem type. Valuable managerial insights are obtained when incorporating carbon emissions cost.
AB - Reverse logistics network design (RLND) is getting momentum as more organizations realize the benefits of recycling or remanufacturing of their end-of-life products. Similarly, there is an impetus for organizations to become more environmentally conscious or green. This environmental context has driven many organizations to invest in green technologies, with a recent emphasis on reducing greenhouse gas emissions. This environmental investment situation and decision can be addressed through the integration of facility location, operational planning, and vehicle type selection, while simultaneously accounting for carbon emissions from vehicles, inspection centers, and remanufacturing centers in a reverse logistics (RL) context. In the current study, we present a mixed-integer linear programming (MILP) model to solve a multi-tier multi-period green RL network, including vehicle type selection. This research integrates facility locations, vehicle type selection with emissions producing from transportation and operations at various processing centers. Prior research does not account for carbon emissions for this design problem type. Valuable managerial insights are obtained when incorporating carbon emissions cost.
KW - 512 Business and Management
KW - Reverse logistics
KW - Remanufacturing
KW - Network design
KW - Mixed integer linear programming
KW - Carbon footprint
UR - http://www.scopus.com/inward/record.url?scp=85075617272&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2019.106184
DO - 10.1016/j.cie.2019.106184
M3 - Article
SN - 0360-8352
VL - 139
JO - Computers & Industrial Engineering
JF - Computers & Industrial Engineering
ER -