Journal
APPLIED SOFT COMPUTING
Volume 95, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.asoc.2020.106554
Keywords
Energy-efficient scheduling; Steelmaking-continuous casting; Temperature; Multi-objective optimization; Local search
Categories
Funding
- National Natural Science Foundation of China [51474044]
- National Key Research and Development Program of China [2017YFB0304005]
Ask authors/readers for more resources
With the increasing energy price and the urgent demand of manufacturing enterprises for energy conservation, energy-efficient scheduling (EES) technology has been widely investigated and applied in industry and academia. The steelmaking-continuous casting (SCC) production is the main energy-consuming sector and the key process for quality control of steel manufacturing. Due to the high-temperature characteristics of SCC production, the temperature drop deriving from nonprocessing process could directly lead to energy loss and increase the energy consumption of each procedure, which has important influence on the total energy consumption. Therefore, the energy-efficient steelmaking-continuous casting scheduling problem with temperature constraints (EESCCSPT) was concerned and a multi-objective mathematical programming model was introduced to minimize the penalty of due date deviation and the extra energy consumption measured by temperature drop. Comparing to the general scheduling problem, the constraint of minimum casting superheat and the constraint of target tapping temperature generated by the high-temperature technical requirements were directly considered to ensure schedule feasibility in terms of temperature. A multi-objective hybrid genetic algorithm combined with local search (MOHGALS) was presented, in which the enhanced evolutionary mechanisms combined with the improved genetic operators and the local search were also designed. Results of computational experiments showed that MOHGALS was more feasible and effective than NSGA-II and SPEA2 on the EESCCSPT. (C) 2020 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available