The Research For Immune Genetic Algorithm And Its Application In The Field Of Job Shoop Scheduling Application

Production scheduling problem exists in various fields. It is the key of manufacturing industry for effective management and operation. The reasonable optimized scheduling strategy can enhance the enterprise's production efficiency and reduce production cost. Therefore, the research of Job-Shop scheduling problem has important theoretical significance and practical significance.As the most widely used evolutionary computation method, the genetic algorithm can be used to optimize production scheduling problem. However, the genetic algorithm has some shortcomings. This paper proposes an improved immune genetic algorithm suitable for this problem, according to the characteristics of biological immune system, such as antigen identification and keeping the diversity of antibodies. Through rational vaccination and immune selection, the diversity of antibodies and the algorithm convergence speed have improved. This can also avoid population degradation and premature convergence and get the global optimal solution. Finally, the paper verifies the job-shop scheduling problem, compares the improved algorithm and traditional genetic algorithm and proves the reasonable and effective of the improved algorithm.