Study On Discrete Production Line Oriented Hybrid Flow Shop Scheduling Problem With Identical Parallel Machine

As high level customer's requirement and increasingly obvious personalized demand,most enterprise's mass production mode also transform into multivariety-small batch production,and realize to not just need consummate production technology and advanced production equipment to improve production efficiency,improve production-management level is more important.Multivariety-small batch production always exists a variety of complicated influencing factors,layout principles?inventory management?quality control method don't solve fundamentally these problems yet.Therefore,scheduling becomes enterprises' the key problem.Reasonable scheduling can not only reduce the waste of resources,decline cost,strengthen the flexibility,but also can improve production efficiency,strengthen management ability.Parallel machine scheduling model exists widely in various fields,to promote the development of the manufacturing industry in our country,solve the parallel machine scheduling problem become the research focus.On the background of hybrid flow shop of discrete production line,the number,type of parts and equipments is known,the goal is minimized the maximum completion time,for searching grey scheduling scheme of identical parallel scheduling combining with eM-Plant simulation software.In this paper,we make the following three aspects:1.The mathematical model is established.Under the background of discrete production line,this paper studies parallel machine of hybrid flow shop scheduling problem,regards adjustment time as the main constraint and minimize maximize the completion time as the optimization goal.The mathematical model is established.2.Simulation analysis of primary optimization.The factory's data is collected,which is used for simulating and optimizing the production status.To prove the effectiveness of the genetic algorithm,the first optimization result is optimized by genetic algorithm;this paper makes use of the convergence of algorithm,to improve the genetic algorithm parameters.New crossover and mutation parameters optimizes completion time.3.Simulation analysis of the second optimization.This paper carrying out the second optimization by changing the initial processing order optimization: according to the specifications of the parts and processing equipment,changing parts order process.New processing technology optimizes completion time.