不确定环境下集成式工艺规划与车间调度中智集建模与优化

Process planning and scheduling are two important functions in a flexible manufacturing system. The integration of the two parts can improve the efficiency of a manufacturing system and the production costs will also be reduced. Nevertheless, manufacturing systems in real world are complex uncertain systems; the idealization of traditional integrated process planning and job shop scheduling models has induced large differences between theoretical research and engineering applications. This project will center on the integrated process planning and scheduling problem under uncertain environment; based on the neutrosophic theory, the mapping relation between uncertain processing time and neutrosophic numbers will be revealed and neutrosophic number based mixed integer programming models with corresponding simplification method will also be constructed. With the features of interval valued neutrosophic sets and single valued neutrosophic sets, the mapping relation between uncertain processing time and the elements of neutrosophic sets will be studied; corresponding uncertain processing time expression methods using neutrosophic sets as well as a fitness evaluation method within the framework of meta-heuristic algorithms will be proposed. On this basis, robust optimization criteria and a multi-objective optimization algorithm will be developed. Moreover, a decision method based on the neutrosophic integral and neutrosophic entropy will be proposed and a MES prototype system that considers uncertain processing time will finally be developed. Findings of this project will enrich and develop both the theory and the technology of intelligent scheduling of manufacturing systems; this also has vast importance to the improvement of the strength of manufacturing industry in China.

工艺规划和车间调度是柔性制造系统的两大关键环节，两者集成优化有助于提升制造系统的效率和降低成本。然而，现实制造系统是复杂不确定系统，传统工艺规划与车间调度集成模型的理想化造成理论与工程应用间存在较大差距。本项目围绕不确定条件下集成式工艺规划与调度问题展开研究；基于中智集理论，揭示加工时间与中智数的映射关系，构建基于中智数的混合整数规划模型并提出模型简化方法。针对区间中智集与单值中智集特点，揭示不确定加工时间与中智集元素间的映射关系、提出不确定加工时间的中智集表示方法并在元启发式算法框架内提出相应适应度评价方法。在此基础上，建立鲁棒性优化指标与多目标算法、构建结合中智积分与中智熵的决策方法、开发考虑不确定加工时间的MES原型系统。本项目研究成果将丰富和发展制造系统智能调度的理论和技术，对于我国制造业实力的提升具有重要意义。

近年来由于产品的设计、制造与管理模式对制造系统提出了较高的要求，将工艺规划与车间调度集成优化已成为先进制造领域的热点问题。然而实际的制造系统是一个异常复杂的不确定系统，集成优化过程中缺乏对不确定因素的考虑将影响或制约制造系统的效率。本研究把加工中的不确定性融入集成式工艺规划与车间调度优化中，建立基于中智集的优化模型与方法：针对工序加工时间不确定性，应用中智集理论，研究加工时间不确定情况下集成式工艺规划与车间调度问题的建模、优化与决策方法并最终得到鲁棒调度方案，实现工艺规划与车间调度充分融合且得到具有鲁棒健壮性的调度方案。本研究提出了基于中智集、中智数的混合整数规划模型，并对集成工艺规划与调度问题进行了建模。提出了基于中智数的memetic算法，特别是提出新的解码过程，得到相应的鲁棒调度方案。研究了不确定加工时间与中智集间的映射关系，将加工时间表示为包含隶属度、不确定度、非隶属度的中智集，提出新的调度解码方法。在多目标优化中，为引导非支配解趋向于偏好区域，提出了中智数环境中基于ε－支配的多目标优化方法，得到了较为理想的Pareto解分布。本项目的研究成果丰富和扩展了中智集理论的应用；通过建立基于中智数的模型，丰富和延伸了传统运筹学的研究范畴、使运筹学从对确定性对象的研究扩展到了对模糊不确定问题的探索；填补了中智混合整数规划研究的空白。本研究还提出基于中智集的元启发式算法以及基于偏好的多目标搜索算法，为基于中智集的调度问题求解提供了新的思路与方法。

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