Research On Steel-making Continuous Casting Production Planning And Scheduling Based On PSO-GA Hybrid Algorithm

Iron and steel industry is the pillar industry of the national economy, as well as the lifeblood in the national economy development. During the process of iron and steel product, quality management, production planning and scheduling, products orders forecast are the focuses and frontier topics in engineering research. Production scheduling is the key element in steel-making continuous casting (SCC) process which is the core of the whole steel production. And a scientific scheduling scheme plays an important role on raising satisfaction rate of customers and strengthening competition ability of enterprises. Based on the complex process of SCC, a mathematical programming model and a hybrid optimization algorithm are proposed to solve SCC planning and scheduling problem, and satisfactory results have been obtained. The main contents are as follows:First, take a depth analysis on steel-making continuous casting produce process, introduces the solutions and achievements in this field.Second, particle swarm optimization (PSO) algorithm and genetic algorithm (GA) areboth evolutionary algorithm (EA). PSO has fast convergent rate, GA has good global performance, but they are different and limited in evolutionary mechanism and application fields. Then, a hybrid optimization algorithm is proposed which is combined particle PSO and GA, and the parameter setting methods and solving steps are given.Third, experimental cases which are under the hybrid flowshop scheduling (HFS) problem model show that, via a large number of HFS basic examples, considered HFS maximum flow time low boundary (LB) as performance evaluation index, compared PSO-GA with PSO under the average relative gap (ARG) optimization strategy, the proposed hybrid algorithm successfully avoid the premature convergence of PSO, guarantee higher accuracy and stability. After that, combined with HFS industry application cases, a mathematical programming model is established whose target is to minimize the maximum production flow time and earliness/tardiness punishment. Via the proposed PSO-GA algorithm, the job scheduling gantt chart is smoothly realized.Fourth, on the basis of all the results above, apply PSO-GA to SCC actual process. To solve the SCC planning and scheduling problem, first of all, SCC process is abstracted as a HFS model. Then, combined with the actual process constraints, analogy to the HFS model, a mixed integer nonlinear programming (MINLP) model is formulated whose aim function is to optimize the maximum production flow time. Meantime, the production scheduling model takes technological characteristics of SCC into consideration, and a linear programming model based on time hindcasting is added to solve job conflicts and optimize waiting time between manufacturing processes. Actual industry data shows that the optimization model and solution strategy can realize continuous casting process and minimize the whole flow time, then improve the equipment usage efficiency so as to acquire an appropriate planning and scheduling results.Finally, the thesis is concluded with a summary and perspectives of some important problems to be solved in the future research.