HPSO-LSA based multi-objective energy consumption optimization for parallel heating furnaces scheduling

The parallel heating furnaces scheduling problem for hot rolling which aims to achieve energy conservation is discussed in this paper. According to the characteristics of parallel heating furnaces, a multi-objective mathematical model is then established considering mixed charging of cold and hot slabs. The model is to minimize the energy consumption of heating furnaces and a hot rolling mill, with the makespan of heating slab as a constraint which makes the loads of furnaces more balanced. A novel Hybrid Particle Swarm Optimization-Local Search Algorithm (HPSO-LSA) is therefore proposed to solve the model. The case study demonstrates the feasibility and effectiveness of the proposed method based on comparison with other existing methods.