Optimization of Slab Location Selection with Markov Characteristics Based on Improved Genetic Algorithm

The optimization of slab location plays a critical role in the management of slab yard, which is related to the efficiency of the subsequent hot rolling process. However, the current slab location recommendation still relies on manual recommendation. In order to realize the automatic production of iron and steel enterprises, a mathematical model that is more in line with the actual production process for the recommendation of slab location is established. And then, an improved genetic algorithm which can solve problems with Markov characteristics is designed to solve this model. Finally, using the data of actual production, the results of the improved algorithm and those of manual recommendation are compared, which proves the feasibility and effectiveness of the model and the improved genetic algorithm. The results demonstrate that the model has high value in practical application and can be used to improve the production efficiency of iron and steel enterprises. Meanwhile, the improved genetic algorithm proposed in this paper provides a new approach to solving problems with Markov characteristics.