基于改进鱼群算法的柔性作业车间调度问题研究

The Research of Flexible Job Shop Problem Based on Improved Artificial Fish Swarm Algorithm

为了解决柔性作业车间调度问题,提出了基于人工鱼群算法的求解方法。针对基本人工鱼群算法后期搜索盲目性大、精度不高的不足,提出了具有分布估计属性的随机行为,在算法中融入了粒子群算法,并采用柔性参数,提高了算法的寻优能力和精度。通过标准Kacem算例对该算法性能进行分析评估,表明了该算法对柔性作业车间调度问题的有效性。

In order to solve the flexible job shop problem（FJSP） , its solution based on the artificial fish swarm algorithm （AFSA）was proposed. In view of blindness and low precision of the basic AFSA in its late stage search, some strategies were presented by the solution, such as the prey behavior with the estimation of distribution, the combination of AFSA with the PS0 algorithm, and the adoption of flexible parameters,in order to enhance search ability and precision of the AFSA. The effectiveness of the algorithm was evaluated by stand- ard kacem sample, and the result demonstrates the effectiveness of the algorithm to solve the FJSP.