| In actual production,enterprises need to allocate resources reasonably to meet the daily production requirements of enterprises.Compared with the traditional job shop scheduling,flexible job shop scheduling is more suitable for the reality of the enterprise workshop.Therefore,more and more scholars begin to study the flexible job shop scheduling problem.At this stage,the solution of most flexible job shop scheduling problems not only needs to consider multiple optimization objectives,but also needs to comprehensively consider the characteristics of flexible production and scheduling performance in the workshop.Although the solution process is complex,it is of great significance to the long-term development of modern manufacturing.Taking the existing job shop scheduling results as the starting point,this paper deeply studies the multi-objective flexible job shop scheduling problem,and establishes a scheduling model aiming at minimizing the maximum completion time,total equipment load,total workshop carbon emission,total workshop energy consumption and delivery time.Compared with the advantages and disadvantages of the existing algorithms,NSGA-Ⅱ algorithm is selected to solve the established job shop scheduling model.NSGA-Ⅱ algorithm shows excellent performance in solving multi-objective problems,but there are still some problems in the process of solving the problem,such as poor convergence and insufficient population diversity.Therefore,this paper makes the following improvements to NSGA-Ⅱ algorithm:first,improve the generation mode of offspring individuals,and determine whether the parent population performs variable neighborhood search operation or cross mutation operation to generate offspring individuals according to the non dominated ranking level and generated random number of individuals in the population,so as to avoid too many duplicate individuals in the population.The second is to improve the selection strategy of elite individuals and add random selection strategy to ensure the diversity of parent population.At the same time,an improved adaptive crossover and mutation operator is proposed to avoid the algorithm falling into local optimization.The improved NSGA-Ⅱ algorithm is applied to the traditional example of job shop scheduling.By comparing the solution results of this algorithm with those of other scholars,the advantages and disadvantages of the improved algorithm are judged.In the comparison results of the objective function,the improved NSGA-Ⅱ algorithm obtains better results when solving the problem,and the problem that the algorithm is easy to fall into local optimization can also be solved.It can be seen that the improved algorithm in this paper has certain effectiveness.Finally,the improved NSGA-Ⅱ algorithm is applied to the actual mold workshop production,and the corresponding workshop scheduling system is designed and developed,which has achieved ideal results. |
