改进蚁群算法的柔性作业车间调度问题研究

Research on Flexible Job Shop Scheduling Problem Based on Improved Ant Colony Algorithm

为提高传统蚁群算法求解柔性作业车间调度问题的效率,提出了一种改进蚁群算法。首先,均匀分布蚂蚁的初始位置;其次,多种方法结合进行机器选择,并按照改进的工序选择方式选择下一步即将遍历的工序;最后,采用带精英策略的蚁群算法结合最大最小蚂蚁系统的信息素更新方式,既赋予较优路径以额外的信息素,同时又对路径上的信息素进行限定、从而避免算法“早熟”,进而提高解的质量。通过三个柔性作业车间调度实例进行仿真分析和与其他算法的对比,结果表明改进蚁群算法在求解柔性作业车间调度问题具有较好的优化效果和求解效率。

In order to improve the efficiency of traditional ant colony algorithm in solving flexible job shop scheduling problems,an improved ant colony algorithm is proposed.First,evenly distribute the initial position of the ants;then,a combination of multiple methods for machine selection,and select the next step to be traversed according to the improved process selection method;finally,the ant colony algorithm with an elite strategy combined with the information of the maximum and minimum ant system The element update method not only gives extra pheromone to the better path,but also restricts the pheromone on the path,so as to avoid the algorithm"premature"and improve the quality of the solution.Through simulation analysis and comparison with other algorithms through three flexible job shop scheduling examples,the results show that the improved ant colony algorithm has better optimization effect and efficiency in solving flexible job shop scheduling problems.