Flexible workshop problem solving based on improved NSGA-II algorithm

Aiming at the problems of multi-objective conflict and uneven resource utilization in flexible manufacturing workshop scheduling, a multi-objective optimization scheduling model is established, which comprehensively takes into account the key indexes such as workshop completion time, energy consumption, delay time and equipment load. In the process of model construction, the mutual influences and constraints among the objectives are fully revealed through the in-depth analysis of the performance indicators in the actual production environment. In order to effectively solve the scheduling model, this paper improves the traditional NSGA-II algorithm by incorporating the greedy algorithm for the fast search of local optimal solutions, which greatly improves the convergence speed and the quality of the algorithm. Meanwhile, the proposed novel solution strategy achieves a good balance between the global search capability of the algorithm and the local fine optimization, and finally the effectiveness of the model is verified by numerical experiments and simulation analysis.