The worker flexibility and green production related factors are two key aspects that widely exit in real-life production and seriously affect the production efficiency and ecological environment, while both of them are usually neglected in the existing scheduling studies. In this paper, a multi-objective flexible job-shop scheduling problem considering worker flexibility and green factors (MO-FJSPG) is explored with the criteria of minimizing makespan, labor cost and green production related factors. A non-linear integer programming model is constructed for MO-FJSPG and a new non-dominated ensemble fitness ranking algorithm (NEFRL) is proposed to solve this problem. In the NEFRL, a specific three-layer representation method is proposed; a non-dominated ensemble fitness ranking method is developed to rank and select solutions for the next generation; a local search method based on critical path is designed to strengthen the exploitation ability of the algorithm and used to optimize the non-dominated solutions further in each iteration. Finally, 31 instances are constructed and the effectiveness of NEFRL is verified by comparing with other multi-objective algorithms.

工人灵活性和绿色生产相关因素是现实生产中广泛存在并严重影响生产效率和生态环境的两个关键方面，而两者在现有调度研究中往往被忽视。在本文中，以最小化完工时间、劳动力成本和绿色生产相关因素为标准，探索了考虑工人灵活性和绿色因素的多目标柔性作业车间调度问题（MO-FJSPG）。针对MO-FJSPG构建了非线性整数规划模型，并提出了一种新的非支配集成适应度排序算法(NEFRL)来解决该问题。在NEFRL中，提出了具体的三层表示方法；开发了一种非支配的集成适应度排序方法来为下一代排序和选择解决方案；设计了一种基于关键路径的局部搜索方法，以增强算法的开发能力，并用于在每次迭代中进一步优化非支配解。最后，构建了31个实例，并通过与其他多目标算法的比较验证了NEFRL的有效性。