Genetic optimization model of steelmaking−continuous casting production scheduling based on the “furnace−caster coordinating” strategy

To avoid the frequent cross supply, excessive waiting time and difficult crane dispatching of molten steel among processes that resulted from the complex workshop layout of the steelmaking continuous casting process, a production scheduling model for the steelmaking-continuous casting process was established in this study with the objective of optimizing and minimizing the total waiting time of all furnaces in the plan. Moreover, an improved genetic algorithm was used to solve the model. In the operation process of the genetic algorithm, the “furnace-caster coordinating” strategy was introduced to improve the quality of the initial population. Furthermore, the crossover and mutation operations were determined based on the comparison of the operating cycles of steelmaking (refining) and continuous casting. The actual production plan under the main production mode of a large domestic steel plant was utilized as the simulation sample. Results show that the performance of the improved algorithm based on the “furnace-caster coordinating” strategy is significantly better than that of the basic genetic and heuristic algorithms. The output of Sample 1 of the main production model 4BOF−3CCM accounts for more than 80% in steel plants. After optimization, the waiting time of the production process is optimized, and the maximum waiting time between steelmaking and continuous casting processes is reduced from 77 to 54 min. The degree of matching of the refining furnace-continuous caster machine is significantly improved. Moreover, the proportion of molten steel poured from the No. 3 refining furnace on the No. 3 continuous caster machine is increased from 25% to 67%. The phenomenon of unclear matching among processes and facilities caused by random facility assignment for one or two furnaces is reduced. Furthermore, the phenomenon of excessive waiting time caused by unreasonable production path for one or two furnaces is reduced. An efficient solution for the study of complex production scheduling problems in steel plants is provided.