Optimization Models And Algorithms For Steel Grade Under Mass Customization

With the proposal of "Industy 4.0" in Germany and the "Made in China 2025 strategy"strategy,the demand of the downstream enterprises is more individualized for steel raw materials.The contradiction between mass production mode and individual demand of multiple varieties and small batch in iron and steel enterprises is more prominent,which brings great difficulties to the production design and production organization of iron and steel enterprises.How to solve the above contradiction has become one of the key problems faced by the iron and steel enterprises.Steelmaking and continuous casting process is located in the upstream of the iron and steel enterprise production process,and it is the key link in the production process of iron and steel products.In this process,the contradiction between the mass production mode and the personalized demand of the customer is mainly reflected in the steel grade design.Based on the actual characteristics of steel grade optimization and design problem,we established the two stage robust optimization model of steel grade design.In order to improve the efficiency of the model,firstly,according to the characteristics of the model,the column-and-constraint generation algorithm is used to solve the problem.Then,the sub-problem is simplified by using dual model.And the KKT condition and strong duality algorithm are used to solve the nonlinear situation.Experiments show that these algorithms can be used to solve small and medium scale problems,but it is difficult to obtain the exact solution of large-scale problems.For this reason,we decompose the problem into a diagonal model on the steel grade group by using the Lagrangian relaxation algorithm because of the phenomenon of steel group in the steel grade design.We design a new iterative step size,direction and termination condition according to the idea of sub-gradient method.Finally,we summarized column-and-constraint generation algorithm based on Lagrangian relaxation decomposition strategy,and the experiment is designed according to the actual production data of the enterprise.The experiment shows that the algorithm can find the exact solution of large-scale problem.In order to solve the urgent steel grade design and optimization problem in iron and steel enterprises,we established an optimization model with high degree of agreement with the actual production process.And we design a series of algorithms to obtain the exact solution of the model.It has certain significance for the guidance of enterprise production or the research of theory and method.