Improved NSGA-II to Solve Flexible Job-Shop Scheduling Problem Considering Random Worker Resignations

As an important production factor in flexible job, human resource dynamic events have an important impact on job scheduling plan. Therefore, this paper studies the flexible job scheduling problem considering the random resignation of workers. A model is established with the maximum completion time and deviation as the optimization objectives, and an improved NSGA-II algorithm is proposed based on the characteristics of the problem. First, an initialization method based on heuristic rules is designed to improve the quality of population initialization; an individual selection scheme based on simulated annealing algorithm is proposed to increase the selection probability of non-excellent individuals and ensure population diversity; an adaptive crossover operator and mutation operator are designed; finally, the tabu search operator is introduced to reduce the number of invalid searches, thereby increasing the overall search scope and capability of the algorithm. The effectiveness and feasibility of the proposed algorithm are verified by comparing the experimental results.