The Research Of Uncertain Job Shop Scheduling Based On Immune Genetic Algorithm

Job Shop Scheduling is an important part of the manufacturing sector,how to use effective methods to optimize scheduling,thus changing the original production management,and to improve the level of production and the competitiveness of enterprises,has always been an important issue.In this paper,processing time fuzzy Job Shop Scheduling problem of the actual production scheduling cases is mainly analyzed,single objective and multi-objective optimization target of uncertain scheduling problem are included.Based immune genetic algorithm and Chaos Search,uses viral mechanisms to improve immune factors,so that the solution in the direction of the optimal solution.And use immune genetic algorithm and non-dominated solution sorting method initially sorting based on Pareto Principle for multi-objective uncertain Job Shop scheduling problem.The research results mainly include the following contents:(1)Firstly,article classify uncertainty and select processing operation mode for class 1 issue in uncertainty,and make the fuzzy theory into the class 1 uncertainty.(2)In this paper,processing time of fuzzy Job Shop Scheduling problem for the actual production scheduling cases is mainly analyzed,using triangular fuzzy number to represent processing time.Immune genetic algorithm and chaotic search algorithm mixed to improve hybrid algorithm,and uses viral mechanisms to improve immune factors which have self-evolution and degradation capacity,so that the solution in the direction of the optimal evolution,makes the best time as the goal,finds the optimal solution to meet customer demand,and the corresponding process is obtained.Through MATLAB and Map of JAVA programming,it proves that the improved algorithm' s feasibility and practicability under uncertain conditions.(3)For multi-objective uncertain Job Shop scheduling problem,non-dominated solutions which based on the principle of Pareto sorted by rapid screening dominated solutions with high levels of improved immune genetic algorithm to find the optimal mix to meet customer demand and its corresponding process route.Using fuzzy numbers describe time parameters and delivery of uncertain Job-Shop Scheduling to construct fuzzy hours-Satisfaction-storage costs scheduling model,and by MATLAB software programming approach,the obtained actual survey data used to make the experiment by improved optimized algorithm,once again proved the feasibility and superiority of optimization algorithm.