Research On Multi-objective Scheduling Optimization Of Flexible Flow Shop

As Internet equipment and the development of information technology and industrialization,manufacturing production level has been improved,and increasing consumer demands for diversified products,has many varieties,small batch production mode has become improve enterprise competition level,rapid response to changes in consumer demand of one of the mainstream mode of production.M Company is a large semiconductor enterprise engaged in the production of silicon wafers,which has the characteristics of diversified products,high personalized demand and high production energy consumption.At the same time,the workshop production process of the enterprise belongs to the problem of flexible flow shop scheduling.Although the enterprise has made some informatization improvement,it has not made full use of its information system at present,especially the production scheduling problems such as mining,processing and analysis of production data.With M company as an example,this paper,the production mode of the flexible flow shop scheduling problem is studied,using the(with elite strategy of rapid non dominated sorting genetic algorithm)algorithm and multi-objective optimization theory,will minimize the total completion time,delay time and the energy consumption cost as shop scheduling optimization goal,in order to enhance the capacity of the optimization of workshop scheduling,Improve the production efficiency and benefit of enterprises.In this paper,according to the production characteristics of flexible flow shop,the maximum completion time,total delay time and total energy consumption cost are selected as the three objective functions of the multi-objective optimization model.After the completion of the construction of the multi-objective scheduling optimization model of flexible flow shop,the NSGA-Ⅱ algorithm was selected to improve,and the improved algorithm was used as the solution algorithm of the model.Secondly,through the survey of M company’s general situation and products and the analysis of workshop scheduling process,it is found that the workshop scheduling has the disadvantages of subjectivity and arbitrariness,which causes many problems to the production of the enterprise.In this paper,the cutting mill workshop of the enterprise is taken as the modeling object,and the improved NSGA-Ⅱ algorithm is used to solve the multiobjective scheduling optimization model of the workshop.Meanwhile,the coverage and overvolume evaluation indexes are compared with the original NSGA-Ⅱ algorithm to verify the superiority of the improved algorithm.Finally,AHP-entropy method is used to set weighting,and a set of Pareto optimal approximate solution set obtained by the improved algorithm is evaluated and selected.The optimized scheduling scheme is superior to the original scheduling scheme in completion time,total delay time,processing cost,equipment utilization ratio and other indicators.