A multi-objective optimization approach for integrated production planning under interval uncertainties in the steel industry

This paper investigates one of the key decision-making problems referring to the integrated production planning (IPP) for the steelmaking continuous casting-hot rolling (SCC-HR) process in the steel industry. The complexities of the practical IPP problem are mainly reflected in three aspects: large-scale decision variables; multiple objectives and interval-valued uncertain parameters. To deal with the difficulty of large-scale decision variables, we introduce a new concept named “order-set” for modeling. In addition, considering the multiple objectives and uncertainties of the given IPP problem, we construct a multi-objective optimization model with interval-valued objective functions to optimize the throughput of each process, the hot charge ratio of slabs, the utilization rate of tundishes and the additional cost of technical operations. Furthermore, we propose a novel approach based on a modified interval multi-objective optimization evolutionary algorithm (MI-MOEA) to solve the problem. The proposed model and algorithm were tested with daily production data from an iron and steel company in China. Computational experiments demonstrate that the proposed method generates quite effective and practical solutions within a short time. Based on the IPP model and MI-MOEA, an IPP system has been developed and implemented in the company.