A Flow Shop with Compatibility Constraints in a Steelmaking Plant* Abstract We present a scheduling methodology for applications where the generation of schedules is constrained by antagonistic and vague Besides temporal and capacity constraints， compatibility constraints between consecutive jobs are We model the vague constraints and uncertain data by fuzzy set The importance of single jobs and the difficulty to schedule them is defined on the different constraints and is used to control the generation of A preliminary schedule is generated by considering the important jobs and those that are difficult to schedule Easy or not so important jobs are scheduled Finally， the achieved schedule is “repaired” until a schedule is found that achieves a given level of Since the goodness of solutions is rated by fuzzy sets， robust schedules achieve better evaluations than weak However， if no robust solution is found constraints will be This methodology is appropriate for applications in process engineering where uncertain knowledge is We explain the methodology with a case study from a steelmaking plant for high-grade steel流动性约束与铺在炼钢厂* 摘要 我们提出一个调度方法的应用产生的时间表而受到限制对立和模糊的知识。除了时间和能力的限制，兼容性限制之间连续工作的管理。我们模型的模糊和不确定的制约因素数据的模糊集理论。单一的重要性和困难的工作安排次 时间是指在不同的制约因素，是用来控制生成的时间表。初步安排是考虑到所产生的重要的工作和那些有困难的时间表第一。容易或不那么重要的工作计划之后。最后，实现的时间表是“修复” ，直到一个时间表，发现达到某一特定的满意程度。因为善良的解决方案是评价模糊集，强大的时间表实现更好的评价比弱时间表。但是，如果没有强有力的解决办法是找到制约将会放宽。这种方法适合于工程应用过程中在不确定性知识为主。我们解释方法，个案研究从炼钢厂的高档钢材。但愿能帮到你，希望采纳！
