TY - JOUR
T1 - A stochastic reverse logistics production routing model with emissions control policy selection
AU - Shuang, Yan
AU - Diabat, Ali
AU - Liao, Yi
N1 - Funding Information:
The research of Mr. Shuang is supported by National Natural Science Foundation of China under grants 71473205 , and Fundamental Research Funds for the Central Universities swu1809014 . Dr. Liao's research is supported by National Natural Science Foundation of China (No. 71871184 and No. 71331004 ) and the Fundamental’ Research Funds for the Central Universities ( JBK150502 and JBK160501 ).
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/7
Y1 - 2019/7
N2 - Carbon emission control policies have emerged in response to the growing global concerns of environmental problems. These regulations should be considered when operational decisions on production, inventory, and routing are being made as emission costs are incurred. In this study, we introduce a reverse logistics supply chain model with remanufacturing and simultaneous pickup and delivery. The problem considers different carbon emission control policies with heterogeneous transportation fleets and allows for lost sales. The aim is to select the optimal carbon control policy with optimal production, inventory, and delivery quantities. The proposed model is formulated as both a deterministic and a two-stage stochastic mixed-integer programming problem. The proposed formulations are demonstrated through two case studies, a simulated reverse logistics supply chain and an actual home appliances production supply chain with remanufacturing options. Sensitivity analyses are conducted to test for the effect of different parameters on the optimal solution. Results indicate that the carbon policy selected has significant effect on the supply chain performance with carbon price being the most significant parameter.
AB - Carbon emission control policies have emerged in response to the growing global concerns of environmental problems. These regulations should be considered when operational decisions on production, inventory, and routing are being made as emission costs are incurred. In this study, we introduce a reverse logistics supply chain model with remanufacturing and simultaneous pickup and delivery. The problem considers different carbon emission control policies with heterogeneous transportation fleets and allows for lost sales. The aim is to select the optimal carbon control policy with optimal production, inventory, and delivery quantities. The proposed model is formulated as both a deterministic and a two-stage stochastic mixed-integer programming problem. The proposed formulations are demonstrated through two case studies, a simulated reverse logistics supply chain and an actual home appliances production supply chain with remanufacturing options. Sensitivity analyses are conducted to test for the effect of different parameters on the optimal solution. Results indicate that the carbon policy selected has significant effect on the supply chain performance with carbon price being the most significant parameter.
KW - Carbon cap-and-trade
KW - Carbon control policy
KW - Carbon tax
KW - Production routing
KW - Reverse logistics
KW - Stochastic demand
UR - http://www.scopus.com/inward/record.url?scp=85063936549&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063936549&partnerID=8YFLogxK
U2 - 10.1016/j.ijpe.2019.03.006
DO - 10.1016/j.ijpe.2019.03.006
M3 - Article
AN - SCOPUS:85063936549
SN - 0925-5273
VL - 213
SP - 201
EP - 216
JO - International Journal of Production Economics
JF - International Journal of Production Economics
ER -