Research On Optimization Of Dual-Resource Batch Scheduling In Flexible Job Shop

Manufacturing is an important cornerstone of a country’s development.With the development of the fourth Industrial Revolution,many emerging technologies have been widely used in manufacturing.China has seized the opportunity brought by the industrial revolution in time and set off the globalization wave of "Made in China".Under the impact of the rapidly changing global market environment,multiple varieties,small batch,customization and compact production cycle have become the main characteristics of China’s manufacturing production mode.Automatic guided vehicle(AGV)and machine tool are important production resources in flexible manufacturing workshop.Batch manufacturing of products and joint scheduling of machine tool and AGV seriously affect the workshop production efficiency,and the time cost of AGV collision detection directly affects the workshop production cycle.Therefore,it is necessary to design and develop a flexible workshop dual-resource batch scheduling optimization platform to provide technical support for subsequent theoretical research and practical application,and intellectual support for the development and design of digital twins.Firstly,combined with the research background and significance of the subject,the research status at home and abroad is summarized,and the organizational structure and research content of the article are clarified.By analyzing the typical characteristics of dual-resource batch production mode,the difficulties of dual-resource batch scheduling problem of flexible job shop were clarified,and the overall optimization process was designed based on the multi-level programming method.Secondly,the advantages and disadvantages of the existing AGV guiding path system in the workshop are analyzed,the AGV guiding path system in the flexible operation environment is determined,and the mapped electronic map model is established.Based on the analysis of AGV conflict types,two conflict resolution strategies are proposed.The improved Dijkstra algorithm is designed based on the time window,and the time consumption cost of the collision free path scheme solved by the algorithm will be an important indicator for solving the double-resource batch scheduling scheme.Then,a nested optimization model is established to minimize the maximum completion time for flexible job-shop batch scheduling with dual-resource constraints.A nested optimization algorithm consisting of improved simulated annealing algorithm and improved genetic algorithm was used to solve the model.Boltzmann acceptance function and variable domain search strategy were introduced into the outer algorithm to improve the search ability of the outer algorithm.The inner algorithm designs the decimal encoding strategy and the activity decoding strategy,realizes the AGV scheduling process by designing the AGV scheduling rules and decoding scheme,and adopts a variety of population initialization strategies and adaptive crossover and mutation probability to improve the search efficiency of the inner algorithm.The batch optimization scheme and dual-resource scheduling scheme are solved by the improved inner and outer layer algorithm.The parameter sensitivity and validity of the algorithm are verified by the calculation case.Finally,the prototype system of dual-resource batch scheduling for flexible shop is designed and developed,and the batch optimization scheme,dual-resource scheduling scheme and path planning scheme of actual production cases are solved by the prototype system.The system is used to simulate the number of AGV configuration in a specific workshop production environment,and the results are analyzed to obtain the impact of the number of AGV configuration on production efficiency.