Flexible scheduling is one of the most significant core techniques for intelligent manufacturing systems. Realization of an optimized schedule through flexible resources assignment is critical to the application and popularization of flexible scheduling, especially in uncertain manufacturing environments. In this paper, we consider flexible job shop scheduling with uncertain processing time represented by fuzzy numbers, which is named fuzzy flexible job shop scheduling. We propose an effective hybrid cooperative coevolution algorithm (hCEA) for the minimization of fuzzy makespan. The hCEA combines particle swarm optimization with the genetic algorithm to improve the convergence ability. A parameter self-adaptive strategy is applied to the problems with different scale effectively as well. Five benchmarks and three large-scale problems with fuzzy processing time are adopted to test the hCEA. Computational results show that the hCEA performs better than the existing methods from the literature.

中文翻译：

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一种用于模糊灵活作业车间调度的混合协作协同进化算法

柔性调度是智能制造系统最重要的核心技术之一。通过灵活的资源分配实现优化的调度对于柔性调度的应用和推广至关重要，尤其是在不确定的制造环境中。本文考虑以模糊数表示的加工时间不确定的柔性作业车间调度，称为模糊柔性作业车间调度。我们提出了一种有效的混合协作协同进化算法 (hCEA)，用于最小化模糊完工时间。hCEA 将粒子群优化与遗传算法相结合以提高收敛能力。参数自适应策略也有效地应用于不同规模的问题。采用五个基准和三个具有模糊处理时间的大规模问题来测试 hCEA。计算结果表明，hCEA 的性能优于文献中的现有方法。