论文部分内容阅读
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 problem of flexible job shop scheduling, a solution method based on artificial fish swarm algorithm is proposed. Aiming at the shortcoming of late search of basic artificial fish school algorithm which is blind and not precise, a random behavior with attribute of distribution estimation is proposed. Particle swarm optimization (PSO) algorithm is incorporated into the algorithm and the optimization ability of the algorithm is improved. Accuracy. The performance of this algorithm is evaluated and evaluated by standard Kacem example, which shows the effectiveness of this algorithm in flexible job shop scheduling.