TY - JOUR
T1 - Cooperative optimization of cutting parameters, process routes, and scheduling considering carbon emissions with analytic target cascading
AU - Tian, Changle
AU - Zhou, Guanghui
AU - Lu, Fengyi
AU - Chen, Zhenghao
AU - Zou, Liang
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
PY - 2021/5
Y1 - 2021/5
N2 - Cutting parameters, process routes, and scheduling significantly affect carbon emissions and makespan of workshops. However, most current researches carried out cutting parameters, process routes, and scheduling decision independently and ignored their comprehensive effects on carbon emissions. To bridge the gap, this paper is aimed at solving cooperative optimization problem of cutting parameters, process routes, and scheduling (CCPJS) employing analytical target cascading (ATC). Firstly, a CCPJS-ATC model is presented and elements of the model are formulated, where carbon emissions and makespan are as optimization objectives. Secondly, a novel-augmented Lagrangian relaxation method is designed to solve the CCPJS-ATC model in a distributed manner. Finally, a case study is employed to verify the feasibility and effectiveness of the proposed method. It shows that the proposed method could achieve more carbon emissions and solving time savings compared with the traditional all-in-one approaches.
AB - Cutting parameters, process routes, and scheduling significantly affect carbon emissions and makespan of workshops. However, most current researches carried out cutting parameters, process routes, and scheduling decision independently and ignored their comprehensive effects on carbon emissions. To bridge the gap, this paper is aimed at solving cooperative optimization problem of cutting parameters, process routes, and scheduling (CCPJS) employing analytical target cascading (ATC). Firstly, a CCPJS-ATC model is presented and elements of the model are formulated, where carbon emissions and makespan are as optimization objectives. Secondly, a novel-augmented Lagrangian relaxation method is designed to solve the CCPJS-ATC model in a distributed manner. Finally, a case study is employed to verify the feasibility and effectiveness of the proposed method. It shows that the proposed method could achieve more carbon emissions and solving time savings compared with the traditional all-in-one approaches.
KW - Analytical target cascading
KW - Cooperative optimization
KW - Low-carbon manufacturing
UR - https://www.scopus.com/pages/publications/85103174064
U2 - 10.1007/s00170-021-06755-7
DO - 10.1007/s00170-021-06755-7
M3 - 文章
AN - SCOPUS:85103174064
SN - 0268-3768
VL - 114
SP - 605
EP - 623
JO - International Journal of Advanced Manufacturing Technology
JF - International Journal of Advanced Manufacturing Technology
IS - 1-2
ER -