在全球市场竞争加剧、资源环境管制增强的形势下，复杂制造系统在环境排放、生产效率和运行状态方面，面临着更严格的要求。 本项目面向复杂工况下柔性加工车间的作业调度，量化其碳足迹，以低碳、高效和平稳为目标，采用元启发式算法构造Meta-Rule。从三个层面实现：①量化工序加工过程的碳足迹，构建碳足迹计算模型；②基于混合整型非线性规划，耦合碳足迹与传统调度指标，建立多目标集成优化模型；③联接预防调度、调度修复与补救、完全重调度方法，研制具有容纳、消除或修复不确定扰动能力的多维度自适应预-反应调度策略。在此基础上，结合基因表达式编程的显式解析优势和模式搜索的全局搜索能力，研制自适应元启发式算法，挖掘出更贴近问题属性的Meta-Rule，以便快速可靠地生成调度方案，更好地满足企业需求。 复杂工况下柔性加工车间的碳足迹规划与调度，优化了生产过程碳效，保证了车间运作稳健，促进了中国制造业的可持续发展。

Modern manufacturing industries have been facing on the global market completion and the environmental pressure. It prompts that the flexible manufacturing system should be lower carbon, more efficient and more stable. For the flexible job shop under complex circumstances, the carbon footprint is quantized. Using the low carbon, efficiency and stability as target, the meta-heuristic algorithm has been applied to establish Meta-Rule automatically. The proposed methodology is realized from three aspects. (1) To quantize the carbon footprint of the operation and construct the carbon footprint model. (2) To construct the complex flexible manufacturing system model based on the mixed integer non-linear programming. (3)To design the multi-dimension prediction-reactive strategy with self-adaptability to respond the uncertain events based on the robust scheduling, the scheduling amendment and the completely rescheduling. Based on the research results, the encoding mechanism of gene expression programming and the framework of pattern search are hybridized. The meta-heuristic algorithm with self-adaptability is proposed to construct Meta-Rule automatically. The Meta-Rule can generate the scheduling scheme quickly and reliably, and satisfy the requirement of the schedulers in the manufacturing company due to its convenience in learning and application. If successful, this project can optimize the carbon footprint and the efficiency, and improve the stability of the manufacturing system concurrently. It also promotes the sustainable development of the manufacturing industry in China.