Optimization method of slab discharge decision model based on quantum-behaved discrete particle swarm

To the slab discharge optimization of steel industry, a class of slab discharge decision model is suggested in this paper, considering the minimal amount of shuffled slab and the minimal crane travel. It consists of the slab discharge optimization decision sub-model and the optimal turned-out slab pile one. The slab discharge planning is accomplished by the layered collaborations between two sub-models. A quantum-behaved discrete particle swarm optimization (QDPSO) algorithm is proposed to solve the first sub-model, where Qu-bit encoding method is designed not only for increasing the ability of DPSO, maintaining the population diversity, but also improving the computing speed of the algorithm. The algorithm can quickly converge to the global optimal solution. The simulation with production data shows that the model and algorithm proposed in this paper are feasible.