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Figure7. The scatter plot for the solutions obtained by IMOEA/DTL and a worker.
In practical applications, the construction of basic data is a particularly critical issue, especially setup-related data, which requires a lot of statistical data. We suggest that a part of the key data can be constructed through the manufacturing execution system, and through the manufacturing execution system, we can know the status of machine, personnel, and materials in real time, and thus make timely responses to emergencies in the production process. In addition, we recommend using commercial production scheduling software and then integrating the model into commercial software. Compared with developing a scheduling system from scratch, this has a higher success rate. 5. Conclusions This study explored a novel energy-saving approach by scheduling under TOU elec- tricity tariffs for tissue paper mills. First of all, an energy cost model was established based on TOU electricity tariffs. The energy cost consists of transportation energy cost, set-up energy cost, and processing energy cost. Second, an energy-efficiency scheduling model was built on the basis of the scheduling model and the energy cost model. Finally, the model was solved by proposing a novel IMOEA/DTL method. The experiment made a comparison between the proposed method and two popular multi-objective optimization methods, MOEA/D-MR, NSGA-II, and SPEA2. The experiment results demonstrate that the proposed method performs better than NSGA-II and SPEA2 in terms of C -metric and HV -metric. Moreover, the proposed method has been proven to have an energy-saving ratio of 2.6% through a real scheduling problem. Considering the similarity between the production processes in tissue paper mills and other papermaking mills, the results are of great reference significance for other papermaking mills. However, this study implemented the algorithms by MATLAB, and the speed of the algorithms should be further improved. Therefore, the speed of the algorithms will be improved in future research. Author Contributions: Conceptualization, Z.Z.; methodology, Z.Z.; software, X.C.; validation, Z.Z., X.C. and K.W.; formal analysis, Z.Z.; investigation, Z.Z., X.C., K.W.; resources, Z.Z.; data curation, Z.Z.; writing—original draft preparation, Z.Z.; writing—review and editing, Z.Z., X.C.; visualization, Z.Z.; supervision, Z.Z.; project administration, Z.Z.; funding acquisition, Z.Z, X.C. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by Natural Science Foundation of Guangdong Province (No. 2020A1515011468); Guangdong University Scientific Research Project (No.2019KTSCX189); Basic Public Research Project of Zhejiang Province (LQ18B060003).
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