Research on low carbon welding scheduling based on production process

The welding workshop of metal structural parts is highly energy-consuming. To meet the national low-carbon green demand, this paper focus on the welding workshop scheduling problem in production process with considering the carbon footprints such as equipment energy consumption, welding material consumption and shielding gas consumption. Firstly, a bi-objective low-carbon welding scheduling mathematical model is established with minimizing makespan and carbon emission. Then, an improved Grey Wolf Optimizer (IGWO) with three strategies is designed to solve this multi-objective problem. The grey wolf multi-wandering strategy (first) is proposed to enhance the population diversity. The grey wolf coordinated hunting strategy (second) based on dynamic weights is introduced to improve the convergence of IGWO. A local optimization strategy(third) is designed to improve the post-optimal search performance by adjusting the machine assignment based on the critical path. A welding workshop green scheduling case is designed to verify the model and algorithm proposed in this paper. The minimum completion time and carbon emissions obtained by the IGWO algorithm are 842.14 and 3.85E + 05, respectively. This result is better than that obtained by NSGA-II and GWO.The results show that the model effectively reduce the carbon emissions of the workshop, and the algorithm can effectively solve the model.

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Publication Details

Journal
Scientific Reports
Published
2024-11-20
DOI
https://doi.org/10.1038/s41598-024-79555-0
Citations
1
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.35

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Research on low carbon welding scheduling based on production process

Z. Y. Wang, Shangkun Deng, Meng Rong, Lei Ding et al.
1 citations
Scientific Reports
Scheduling and Optimization Algorithms
0.35
article

Research on low carbon welding scheduling based on production process

Z. Y. Wang, Shangkun Deng, Meng Rong, Lei Ding, Wei Zeng, Feng Guan, Zhongren Wu
article en
1 citations

Abstract

The welding workshop of metal structural parts is highly energy-consuming. To meet the national low-carbon green demand, this paper focus on the welding workshop scheduling problem in production process with considering the carbon footprints such as equipment energy consumption, welding material consumption and shielding gas consumption. Firstly, a bi-objective low-carbon welding scheduling mathematical model is established with minimizing makespan and carbon emission. Then, an improved Grey Wolf Optimizer (IGWO) with three strategies is designed to solve this multi-objective problem. The grey wolf multi-wandering strategy (first) is proposed to enhance the population diversity. The grey wolf coordinated hunting strategy (second) based on dynamic weights is introduced to improve the convergence of IGWO. A local optimization strategy(third) is designed to improve the post-optimal search performance by adjusting the machine assignment based on the critical path. A welding workshop green scheduling case is designed to verify the model and algorithm proposed in this paper. The minimum completion time and carbon emissions obtained by the IGWO algorithm are 842.14 and 3.85E + 05, respectively. This result is better than that obtained by NSGA-II and GWO.The results show that the model effectively reduce the carbon emissions of the workshop, and the algorithm can effectively solve the model.

Scientific ReportsVol. 14(1)
China Three Gorges Corporation (China) (CN), China Three Gorges University (CN), Wuhan University of Technology (CN)
National Natural Science Foundation of China, China Three Gorges University, Natural Science Foundation of Hubei Province
Openalex Percentile: Top 33%
Scheduling and Optimization Algorithms
0.35
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