【摘要】 燃气表检测线的调度问题是典型的柔性开放车间调度问题。针对该问题，以最小化最大完工时间为目标提出了一种混合麻雀搜索算法（HSSA）。首先，根据问题特性设计有效的编码方式，建立了连续空间与离散空间的映射关系；然后，通过混合拟反向学习等多种策略改进原麻雀算法的种群生成方式和寻优机制，增强了算法的勘探能力和开发能力；最后，基于Taillard标准实例和燃气表检测线应用实例进行实验，并与其他算法对比。结果表明，HSSA在求解燃气表检测线调度问题时具有更高的寻优精度，并验证了该算法的有效性和稳定性。更多还原

【Abstract】 The scheduling problem of the gas meter detection line is a typical flexible open shop scheduling problem.Aiming at this problem,a hybrid sparrow search algorithm(HSSA) is proposed with the goal of minimizing the maximum completion time in this paper.Firstly,an effective coding method is designed according to the characteristics of the problem,and the mapping relationship between continuous space and discrete space is established.Secondly,the population generation mode and optimization mechanism of the original Sparrow algorithm are improved through a variety of strategies such as quasi-oppositional learning,which enhances the algorithm’s exploration and development capabilities.Finally,based on the Taillard standard example and the application example of the gas meter detection line,the experiment is compared with 5other algorithms.The results show that HSSA has higher optimization accuracy when solving the gas meter detection line scheduling problem,and verifies the effectiveness and stability of the algorithm.更多还原