Application Research Of The Improved Niche Genetic Algorithm In Multi-objective Job Shop Scheduling

Shop scheduling problem is an important part of computer integrated manufacturing systems engineering,and it has an important imapct on enterprises'production and management.With the development of global economy,the markets'competition is more and more fierce.Manufacturing enterprises must be react quickly with markets'diversification in order to use the smallest resource consumption to produce high-quality products quickly.Formerly shop scheduling system can only be used to adapt to a specific shop environment and can only get the shortest time,ordinary equipment load balance,which will seriously affect enterprise'development. In this paper,according to the shortcomings of formerly shop scheduling system, multi-objective jobs shop scheduling system is proposed,which requires an efficient optimal scheduling algorithm.Many manufacturing raising scheduling problems are very complicated,and they are difficult to solve using traditional optimization algorithm.In recent years, the genetic algorithm as an optimization algorithm for solving shop scheduling is researched by the vast number of scholars.In this paper,author does a great deal of research and analysis genetic algorithm,and find that the traditional genetic algorithm to solve shop scheduling easily lead to local problems and slowly convergence speed.According to the problem,an improved niche genetic algorithm is proposed.The new algorithm uses a dynamic method to determine the distance parameter of the niche,which does good to form a better niche environment for populations;Using the method of the comparison of allele to judge the individual whether or not similar within distance parameter,which avoids the optimal individual being eliminated,and improves the search efficiency of the algorithm.The establishment of initial population uses niche technology which is proposed in this paper.The average fitness of initial population is high,and it helps algorithm fast search towards the direction of solution.Through multi-objective optimization test function and the actual production model of the workshop demonstrates the new algorithm's high efficiency. New algorithm can successfully search for the optimal solution or the Pareto solution set.According to a factory's practical problems, this paper designes and achieves the multi-objective job shop scheduling system which is based on the technology of .net.Using new algorithm for solving the actual shop scheduling problem,which can get four optimization objectives'Pareto solution set and the result is feasible and effective.The four optimization objectives includes processing time, processing costs, ahead of time and extension of time.