Master production schedules (MPS) and Material requirements planning (MRP) are two important planning modules in the production planning system. In this paper, a new fuzzy credibility-based double-sided chance-constrained programming (FCDCP) model is proposed for the capacitated MPS/MRP integrated programming problem under complex uncertainty. The proposed model supports simultaneous lot sizing and scheduling decisions and can deal with uncertainty presented as fuzziness in both right-hand and left-hand sides of constraints. To tackle the FCDCP model, the corresponding defuzzification methods based on credibility measure are proposed for transforming the fuzzy MPS/MRP integrated programming model into a crisp equivalent mixed-integer programming model. When decision-makers decide on MPS/MRP integrated programming problem, the optimal lot sizing and scheduling solutions from the FCDCP model can not only provide an effective method for production planners to deal with the uncertainty in the production system, making the production plan more reasonable and accurate, but it can also help decision-makers obtain the optimal production plans and determine the best allocation of production resources, effectively reducing the total cost of the production system. Finally, an industrial example from a transmission manufacturer is provided to show the applicability and flexibility of the model.

主生产计划（MPS）和物料需求计划（MRP）是生产计划系统中的两个重要计划模块。针对复杂不确定条件下的带容量MPS / MRP集成规划问题，提出了一种基于模糊可信度的双面机会约束规划（FCDCP）模型。所提出的模型支持同时进行批量确定和调度决策，并且可以处理在约束的右手侧和左手侧都表现为模糊性的不确定性。针对FCCDP模型，提出了相应的基于可信度度量的去模糊方法，将模糊MPS / MRP集成规划模型转换为清晰的等价混合整数规划模型。当决策者决定MPS / MRP集成编程问题时，FCDCP模型中的最佳批量确定和排产解决方案不仅可以为生产计划人员提供一种有效的方法来应对生产系统中的不确定性，使生产计划更加合理和准确，而且还可以帮助决策者获得决策依据。优化生产计划，确定生产资源的最佳配置，有效降低生产系统的总成本。最后，提供了变速箱制造商的工业示例，以显示该模型的适用性和灵活性。但它也可以帮助决策者获得最佳的生产计划并确定最佳的生产资源分配，从而有效地降低了生产系统的总成本。最后，提供了变速箱制造商的工业示例，以显示该模型的适用性和灵活性。但它也可以帮助决策者获得最佳的生产计划并确定最佳的生产资源分配，从而有效地降低了生产系统的总成本。最后，提供了变速箱制造商的工业示例，以显示该模型的适用性和灵活性。