Research On Hot Strip Mills Load Distribution Strategies Based On Ant Colony Optimization Algorithm

Hot Strip Mills load distribution is to determine the value of press load distribution of each step according to the intermediate slab information and production specification under the full consideration of relevant constraints. The load distribution is the core part of rolling schedule. The reasonable one should not only make rolling mill get the full use of rolling ability but also give the better working start points to the flatness control system and the thickness control system. Therefore, the study on load distribution of Hot Strip Mills has very important realistic meanings.Since the load distribution strategy based on experience which is widely used in industrial field is feasible but not optimal, in this thesis, the flatness and thickness of the strip are set as the optimized targets and the optimization model is established based on the mathematical model. The strategy of Hot Strip Mills load distribution based on Ant Colony Optimization Algorithm is conducted in-depth research. The main work and results are as follows:Firstly, through the methods of the discretization of decision variables and weighted summation of objective functions, the Ant System Optimization Algorithm is applied to Hot Strip Mills load distribution. Then the strategy of Hot Strip Mills load distribution based on Ant System Algorithm is proposed and the validity of this method is proved by simulation. On the basis of theoretical research, AS algorithm is applied to the Level-2 system of the simulation platform. The load distribution of different strips can be optimized through the Level-2 system by invoking the AS algorithm.Secondly, through the further research of Ant Colony Algorithm, the Multi-objective Continuous Ant Colony Optimization Algorithm is presented. In the MOCACO Algorithm, ants crawl in the continuous space, and the ant pheromones are only retained in the current position and pheromones are updated according to Pareto dominance relationship. A set of non-dominated solutions can be obtained after once optimization. On the basis of MOCACO, Ant Colony Algorithm for multi-objective optimization of Hot Strip Mills distribution is proposed and the superiority of the MOCACO Algorithm in solving the problem of Hot Strip Mills load distribution is proved by simulation experiments.Finally, the applicability and practical value of both AS Algorithm and MOCACO Algorithm are summarized.