Research On Gear Job Shop Scheduling Problem Based On Evolutionary Algorithm

Manufacturing is the main body of the national economy,is the foundation of a strong country,the rejuvenation of the country,the foundation of a country.Gear manufacturing industry is the backbone of the development of China’s manufacturing industry.With the innovation of technology,intelligent manufacturing is more and more favored by gear manufacturing enterprises,and the job shop scheduling optimization technology in intelligent manufacturing directly affects the high efficiency,low cost and high reliability of manufacturing enterprises.The classic workshop scheduling problem can not be quickly applied to the new manufacturing mode,and the flexible job shop scheduling problem breaks through the unique constraint of processing resources in the traditional problem,more in line with the development needs of gear manufacturing enterprises.The change of the industrial era leads to a single performance index no longer meeting the needs of the long-term development of enterprises,and enterprises need to follow the trend of social development to achieve balanced development.Therefore,starting from the actual gear production workshop,after weighing the advantages and disadvantages,establishing a multi-goal flexible gear operation workshop scheduling model to minimize the maximum completion time,production cost and customer reputation.For the flexible gear job shop scheduling model,the weight coefficient method is used to transform multi-objective performance index into single objective performance index.An improved evolutionary algorithm is proposed.The algorithm is based on genetic algorithm and uses the advantage of simulated annealing algorithm to jump out of local optimal solution,to enhance the local search ability of the algorithm.Elite storage strategy is adopted to timely store high-quality individuals after genetic manipulation to avoid loss.In addition,an improved adaptive crossover mutation probability formula is used to generate dynamic crossover mutation probability to improve the performance of the algorithm,such as search optimization and convergence speed.The effectiveness of the algorithm is verified by using the flexible job shop standard examples.Finally,the actual gear job shop was inspected,and a gear job shop scheduling system adding this algorithm was compiled through MATLAB GUI tool.The system has the functions of login interface,data entry,scheduling execution,result display and other functions,which basically meets the scheduling arrangement of the daily work of the gear operation workshop.