"数字孪生车间调度管理系统构建"

车间调度是智能制造中的一个关键问题，为了满足日益增长的智能化生产需求和车间生产效率要求，需要提出更高效稳定且性能更好的生产调度算法。然而，在当前的车间生产管理过程中，物理空间和信息空间缺乏互通，无法满足智能化生产的需求。因此，数字孪生作为一种新的思想出现，为实现生产车间有效调度管理提供了新的思路。 本文主要针对蜜蜂进化型遗传算法进行改进，通过设置汉明距离来优化初始化种群，采用分阶段选择策略和种群舍弃算子，同时将简化后的模拟退火操作融入到蜜蜂进化型遗传算法中。通过这些改进，可以提高车间调度的效率和稳定性，从而满足智能制造的需求。 关键词：数字孪生，车间调度，生产管理，蜜蜂进化型遗传算法，汉明距离，模拟退火操作 Abstract: In recent years, manufacturing technology is constantly developing towards intelligence, and the scheduling problem in the workshop production process is an important research object for intelligent manufacturing. In response to the increasing demand for intelligent production and the requirements for workshop production efficiency, more efficient, stable, and better performance scheduling algorithms should be proposed. However, in the current workshop production management process, the lack of communication between physical space and information space cannot meet the needs of intelligent production. Therefore, the emergence of digital twins as a new idea provides a new approach to effective scheduling and management of production workshops. This paper focuses on the improvement of the bee evolutionary genetic algorithm, optimizing the initial population by setting the Hamming distance, adopting a phased selection strategy and population abandonment operator, and integrating the simplified simulated annealing operation into the bee evolutionary genetic algorithm. Through these improvements, the efficiency and stability of workshop scheduling can be improved to meet the needs of intelligent manufacturing. Keywords: Digital twins, workshop scheduling, production management, bee evolutionary genetic algorithm, Hamming distance, simulated annealing operation.