Research On Flexible Job Shop Scheduling Optimization Under Uncertain Factors

Shop scheduling is an important part of manufacturing process.Compared with traditional job shop,flexible job shop can deal with the relationship between processing equipment,workpiece and production management more effectively.In the actual production and manufacturing process,there are more and more uncertainties that factors affect the smooth progress of processing,which makes it difficult to obtain some production data accurately and can not be processed smoothly according to the scheduling scheme.Therefore,analyzes the uncertainties existing in the flexible job shop scheduling problem,this thesis studies the flexible job shop scheduling problem under uncertain processing time and random machine faults,establishes a mathematical model,solves the model by improving the brainstorming optimization algorithm,and designs the flexibility under uncertain factors.The above provides an effective solution to flexible job shop scheduling problem.The main research contents of this thesis are as follows:On the basis of comparative analysis of the types and characteristics of job shop scheduling,flexible job shop scheduling was selected as the research object,combined with the characteristics of uncertainty and multi-objectives of flexible job shop scheduling,the optimization system framework of flexible job shop scheduling problem under the uncertain factors was constructed.Analyze the key technologies such as uncertainties,model building and solution algorithms involved.Analyzed uncertain factors and established a mathematical model considering uncertain processing time and random machine failure.Based on the analysis of the uncertain factors in the scheduling problem of the job shop,the uncertain processing time and random machine failure factors are studied.Aiming at flexible job shop scheduling problem considering uncertain machining time,a mathematical model of flexible job shop scheduling considering uncertain machining time was established based on fuzzy number theory.Aiming at flexible job shop scheduling problem considering random machine faults,a mathematical model of flexible job shop scheduling based on hybrid rescheduling strategy and combined rescheduling method was established under random machine faults.A flexible job shop scheduling optimization algorithm is designed.A set of proprietary coding methods for solving flexible job shop scheduling problems are adopted.In view of the low convergence speed of the brainstorming optimization algorithm and the shortcomings of local optimal solution,an improved brainstorming optimization algorithm for single-target and multi-target problems is proposed respectively,and the test function is used for simulation analysis to verify the proposed improvements.The algorithm can effectively improve the convergence speed and accuracy of the algorithm.And use the improved brainstorming optimization algorithm to solve the flexible job shop scheduling problem,the solution results show the effectiveness of the improved algorithm to solve the flexible job shop scheduling problem,and lay the foundation for the subsequent solution of the FJSP optimization problem under uncertain factors.Optimization design of flexible job shop scheduling problems considering uncertain processing time and random machine failures.For the flexible job shop scheduling mathematical model that considers uncertain processing time,the improved brainstorming optimization algorithm is used to carry out single-target and multi-target optimization solutions aimed at satisfaction,fuzzy maximum completion time and fuzzy maximum machine processing load respectively.The solution results show that multi-objective optimization can better balance the relationship between each optimization goal;for the mathematical model of flexible job shop scheduling under the consideration of random machine failure,use the improved brainstorming optimization algorithm to solve the single-target and multi-target optimization solutions aimed at the maximum completion time,machine processing energy consumption and equipment load variance respectively,and add the re-scheduling scheme.The analysis of the work data shows that the two rescheduling strategies have different focuses and reflect the effectiveness of the rescheduling strategy.The results of multi-objective optimization solution for the random machine failure problem under uncertain processing time show that the completed process will have an impact on the generation of subsequent rescheduling scheme,and the multi-objective optimization design solution can better reflect the accuracy of the scheduling scheme.In order to facilitate the development of a flexible job shop scheduling prototype system that considers uncertainties,it adopts front-end and back-end separation technology,based on frameworks such as Vue and SpringBoot,and designs the functional modules of the scheduling system by analyzing the functional requirements of the system to realize the functions of processing information management and re-scheduling scheme generation,providing a solution for the flexible job shop scheduling production considering uncertainties.