In this study, an optimization of supply chain network for New Energy Vehicle Power Batteries
(NEVPB) from the perspective of resource circulation is proposed. The model consists of seven
stages in terms of collection center (CC), repairing center (RC), distribution center (DC), recycling
center (RY), part supplier (PS), material supplier (MS), and disposal center (DP).
The model is formulated as a nonlinear integer programming model and a comparison of LINGO
and genetic algorithm (GA접근법) are conducted respectively.
In numerical experiment, it has found a way to repair and recycle NEVPB. Retrieving as many
NEVPBs in use demonstrates sustainable power generation benefits by maximizing the use of
recovery through resource recycling and searching for recovery classification of batteries as well as
shortening lifespan that occur during the process of producing initial parts and modules from raw
materials.
In this study, an optimization of supply chain network for New Energy Vehicle Power Batteries
(NEVPB) from the perspective of resource circulation is proposed. The model consists of seven
stages in terms of collection center (CC), repairing center (RC), distribution center (DC), recycling
center (RY), part supplier (PS), material supplier (MS), and disposal center (DP).
The model is formulated as a nonlinear integer programming model and a comparison of LINGO
and genetic algorithm (GA접근법) are conducted respectively.
In numerical experiment, it has found a way to repair and recycle NEVPB. Retrieving as many
NEVPBs in use demonstrates sustainable power generation benefits by maximizing the use of
recovery through resource recycling and searching for recovery classification of batteries as well as
shortening lifespan that occur during the process of producing initial parts and modules from raw
materials.