Application Research Of Scheduling Generation Optimization Method Based On Genetic Algorithm In Manufacturing Execution System

China's space industry was formally born in 1956.During the past 60 years,China's space industry has now entered the world's list of large aerospace countries through generation by generation's endeavor of aerospace workers.With the continuous development and progress of China's space industry,challenges appeared in the fields,for example,research,production and management of the aerospace research institutes and companies.Therefore,an aerospace company will accelerate the pace of information construction.The main content of the construction will focus on product development process management and product development site management,methods to ensure the continuous improvement of production process management and quality monitoring capabilities,and ways to effectively deal with the changes in the manufacturing plan are the main issues of the company.Therefore,it is necessary to establish a manufacturing execution system with the company's own characteristics,including management and optimization of various factors of production plan,order management,and quality and other aspects.All the actions above contribute to the management of information management which can improve the production of the company.This paper introduces the manufacturing execution system(MES)in M Space Company,and found some factors that affect productions scheduling through the research of the enterprise production scheduling.For example,only through experience and the historical data to estimate the orders can not minimize total completion time and distribute processing resources from the standpoint of global optimization.Firstly,in this paper,depend on the genetic algorithm,the optimized model of the production scheduling problem has been set up,use the new strategy of encoding and gained better results.Secondly,after analyzing the simulation results from the basic genetic algorithm,found that the results are easy to fall into local optimization.At the same time,the results endured with slow convergence to the global optimum.Thus,using the elitism strategy,choosing the former better individual directly into the next generation,to improve the speed of convergence to the global optimum.At the same time,in dealing with practical problems,the fault-tolerant of different solution may lead to different performance.Thus,in order to solve the problem of production scheduling through genetic algorithm,fault-tolerant capability of various solutions have been taken into consideration.The concept of saturation is raised to improve the variety of the population.The accuracy and efficiency of the improved method are verified by simulation results.Finally,from the perspective of the UML model,this paper analyzes the existing problems in manufacturing execution system and manufacturing process requirement of the M space company;research the design and implementation method on manufacturing execution system.The basis of functional implementation,the improved manufacturing execution system has been applied.The results illustrated that the efficiency of production line have been highly improved.Combined with the network interface of related equipment,this paper studied and solved the related integration problems of system and device interface.This paper takes the manufacturing execution system of M Space Company as research,analyzes and improves the genetic algorithm and enhance the stability and fault tolerance of the genetic algorithm.Then apply genetic algorithm to scheduling algorithm.The results of experiments proved the correctness of the algorithm.The improved genetic algorithm can be applied to the manufacturing execution system of M Space Company,so as to improve the management and production capability of the company,and contribute to the development of China's space industry.