Abstract We consider the job shop scheduling problem with fuzzy sets modelling uncertain durations and flexible due dates. With the goal of maximising due-date satisfaction under uncertainty, we first give a new measure of overall due-date satisfaction in this setting. Then, we define a neighbourhood structure for local search, analyse its theoretical properties and provide a neighbour-estimation procedure. Additionally, a tabu search procedure using the neighbourhood is combined with a genetic algorithm, so the resulting memetic algorithm, guided by the defined due-date satisfaction measure, is run on a set of benchmarks. The obtained results illustrate the potential of our proposal.

中文翻译：

---

模糊作业车间调度中灵活到期日满意度的进化禁忌搜索

摘要 我们考虑了具有不确定工期和灵活到期日的模糊集建模的作业车间调度问题。为了在不确定性下最大化到期日满意度，我们首先在这种情况下给出了总体到期日满意度的新衡量标准。然后，我们为局部搜索定义了一个邻域结构，分析了它的理论特性并提供了一个邻域估计程序。此外，使用邻域的禁忌搜索程序与遗传算法相结合，因此得到的模因算法在定义的到期日满意度度量的指导下，在一组基准上运行。获得的结果说明了我们提议的潜力。