Research On Hybrid Flow Shop Scheduling Using Mixed Genetic Algorithm Based On Petri Net

Mixed flow manufacturing is a production organization mode that takes customer needs as the guide and basically does not change the production capacity of the workshop,simultaneously processing and assembling multiple types of products in a manufacturing mode in a mixed manner.It is a modern customized production method produced in order to meet the diversified needs of the market and customers,and is widely used in the real manufacturing industry.When many types of workpieces are processed on limited equipment resources under certain technical constraints,scheduling issues are involved.Scheduling problem refers to satisfying the required objective function value by optimizing the limited production resources in the system.Therefore,strengthening the optimization of mixed-flow manufacturing scheduling has great practicality for improving equipment utilization,reducing the completion time of workpieces,enhancing market competitiveness,and improving enterprise efficiency.This subject takes the manufacturing process of copper clad laminate of a large-scale enterprise in Dongguan as the research background.The production process of this product is a mixed-flow workshop scheduling problem with two processing steps and a large number of parallel machines with the same(equivalent machine efficiency)and nonequivalent(different machine efficiency).First of all,for a large number of parallel machines in the workshop,a modeling method for the ability to provide resources in the manufacturing process is proposed.By mapping the same type of resources in the production line to the same node in the Petri net,a Petri Nets-based model is established.The hybrid manufacturing model(Hybrid Manufacturing Petri Net,HMPN)has greatly reduced the scale of the mixed manufacturing process and provided convenience for analyzing scheduling optimization problems.Then,based on the HMPN model,with the minimum objective completion time as the scheduling objective function,a hybrid Genetic Simulated Annealing Algorithm(GASAA)was designed to optimize the scheduling problem in the HMPN model.By adding the operation of Simulated Annealing(SAA)to the Genetic Algorithm(GA),the overall optimization effect is improved.In addition,the parameters used in the hybrid genetic algorithm are efficiently configured by using the Taguchi experimental method.The HMPN model and the hybrid algorithm program are written in MATLAB,and the effect of the hybrid genetic algorithm is confirmed by the simulation experimental data.A large number of experimental results show that the hybrid genetic algorithm based on the Petri net model designed in this topic solves the scheduling problem of mixed flow manufacturing,whether it is in terms of global optimization ability or algorithm solving efficiency,etc.Better results.By using a hybrid genetic optimization algorithm,the overall optimization effect is improved,and the rationality of this paper is verified.