Research On Flexible Job Shop Scheduling Problem In Smart Factory Considering Workpiece Release Time

With the development of science and technology,the global manufacturing industry is gradually developing towards the direction of digitization and intelligence.Many problems such as low production efficiency,high energy consumption,and poor reliability in traditional manufacturing have become increasingly prominent.As a result,smart factories came into being in the context of Industry 4.0 and Made in China 2025,which was the symbol of the beginning of the fourth industrial revolution,and also brought important opportunities for countries to seize the commanding heights of intelligent manufacturing technology and enhance industrial competitiveness.At the same time,smart factories still face many problems and challenges in the application process of automotive electronics,marine machinery,aerospace and other fields.Based on this,this paper introduces the development status of smart factories.At the same time,combined with the research status of flexible job shops in smart factories,it expounds the problems that still need to be solved in the current research of flexible job shop scheduling problem(FJSP).It includes the following several aspects of research.First of all,this paper proposes an improved wolf pack optimization algorithm(Improved Discrete Wolf Pack Algorithm),hereinafter referred to as IWPA algorithm.In view of the shortcomings of the traditional wolf pack algorithm(hereinafter referred to as the WPA algorithm),the initial solution quality is poor,the global search ability is not strong enough,and the exploration ability and development ability are poorly balanced.Corresponding improvements have been made,and the performance of the improved IWPA algorithm has passed 15 tests.The function is verified and compared with the convergence of the pre-improved WPA algorithm,the improved particle swarm algorithm(DPSO)and the cuckoo algorithm(CS).The test results show the effectiveness of the improved strategy of the IWPA algorithm.Secondly,this paper applies the improved IWPA algorithm to the research of flexible job shop scheduling,and establishes a mathematical model of the basic flexible job shop scheduling problem with the maximum completion time as the optimization goal,through the steps of encoding,decoding,continuous-discrete transformation,iterative optimization and etc.to solve the model.At the same time,the improved IWPA algorithm is compared with other related algorithms for solving FJSP problems through the FJSP test set and actual cases.Finally,this paper proposes a multi-objective flexible job shop scheduling model(RMOFJSP)considering workpiece release time and an improved NSGA-Ⅱ algorithm(GNSGA-Ⅱ)for multi-objective problems.Based on the RMOFJSP model,the improved NSGA-Ⅱ algorithm is used to solve the Pareto optimal solution set,and the comparison experiments are carried out with the MOFJSP model without considering the release time and the unimproved NSGA-Ⅱ algorithm.The results verify that the release time affects the scheduling solution.Impact and effectiveness of improved strategies for the NSGA-Ⅱ algorithm.