Research on modeling and solving algorithm of steelmaking continuous casting production scheduling

As a large-scale industrial consumer, the efficient and stable operation of iron and steel industry has an important impact on the development of national economy. In this paper, the modeling and solving algorithm of steelmaking continuous casting production scheduling process are studied in detail. First of all, considering the stability of the system operation and the timely completion of the production plan, the two objective functions are to minimize the advance/delay time of all casts and the makespan, respectively. Secondly, based on the analysis of steelmaking continuous casting process, a variety of process constraints are proposed. Combining with the two objective functions, the steelmaking continuous casting production scheduling problem model is constructed. Then, aiming at the shortcomings of the traditional particle swarm optimization (PSO) algorithm and genetic algorithm (GA), the improved particle swarm optimization (IPSO) and improved genetic algorithm (IGA) are proposed, and IGA-IPSO algorithm is proposed by combining them. Finally, five different algorithms are used to solve the proposed model, and the results show the superiority of IGA-IPSO algorithm in solving the proposed model.