Flexible job shop scheduling has been widely researched due to its application in many types of fields. However, constraints including setup time and transportation time should be considered simultaneously among the realistic requirements. Moreover, the energy consumptions during the machine processing and staying at the idle time should also be taken into account for green production. To address this issue, first, we modeled the problem by utilizing an integer programming method, wherein the energy consumption and makespan objectives are optimized simultaneously. Afterward, an improved Jaya (IJaya) algorithm was proposed to solve the problem. In the proposed algorithm, each solution is represented by a two-dimensional vector. Consequently, several problem-specific local search operators are developed to perform exploitation tasks. To enhance the exploration ability, a SA-based heuristic is embedded in the algorithm. Meanwhile, to verify the performance of the proposed IJaya algorithm, 30 instances with different scales were generated and used for simulation tests. Six efficient algorithms were selected for detailed comparisons. The simulation results confirmed that the proposed algorithm can solve the considered problem with high efficiency.

灵活的车间调度由于其在许多领域中的应用而被广泛研究。但是，在实际需求中应同时考虑包括建立时间和运输时间在内的限制条件。此外，对于绿色生产，还应考虑到机器加工过程中和处于空闲状态时的能耗。为了解决这个问题，首先，我们通过使用整数编程方法对问题进行建模，其中同时优化了能耗和制造目标。之后，提出了一种改进的Jaya（IJaya）算法来解决该问题。在提出的算法中，每个解决方案都由二维向量表示。因此，开发了一些特定于问题的本地搜索运算符来执行开发任务。为了提高探索能力，在算法中嵌入了基于SA的启发式算法。同时，为了验证所提出的IJaya算法的性能，生成了30个具有不同比例的实例并将其用于仿真测试。选择了六种有效算法进行详细比较。仿真结果表明，该算法可以高效地解决所考虑的问题。