遗传算法在卷包车间提效分析的应用研究

Application of Genetic Algorithm in Efficiency Improvement Analysis of Cigarette Workshop

中文关键词:  卷包车间  遗传算法  车间调度  数学模型

英文关键词:cigarette workshop  genetic algorithm  workshop scheduling  mathematical model

中文摘要:

      目的 卷烟车间是卷烟生产中的重要环节，其生产效率的高低直接关系到企业的经济效益和市场竞争力。车间调度是卷烟车间生产过程中的关键环节，通过优化生产资源，提高生产效率和经济效益，从而保证产品质量和生产周期。方法 通过建立数学模型，描述车间的生产流程，运用优化技术求解模型，以最小化任务完成时间为优化目标。结合车间实际情况，采用改进遗传算法进行求解。结果 经优化后，最大完工时间的最小值为614，在90代左右进入收敛状态。结论 验证了优化算法在解决车间调度问题中的有效性和实用性，优化后的调度方案可以大幅提高车间生产效率、降低生产成本。

英文摘要:

      The cigarette workshop plays an important role in cigarette production, and its production efficiency is directly related to the economic benefits and market competitiveness of enterprises. Workshop scheduling is a key issue in the production process of the cigarette workshop. The work aims to optimize production resources to improve production efficiency and economic benefits, thus ensuring product quality and production cycle. By establishing a mathematical model, the production process of the workshop was described and the optimization techniques were adopted to solve the model, with the optimization goal of minimizing task completion time. Combined with the actual situation of the workshop, an improved genetic algorithm was used to solve the problem. The optimal maximum completion time was minimized to 614, entering a convergence state around the 90th generation. The effectiveness and practicality of the optimization algorithm in solving workshop scheduling problems have been verified. The optimized scheduling scheme can significantly improve workshop production efficiency and reduce production costs.