基于遗传算法的柔性车间调度优化

Scheduling Optimization of Flexible Job-shop Using Genetic Algorithm

针对传统作业车间调度存在加工设备功能单一、加工工序对应设备固定的问题,提出一种新型混合改进的遗传算法进行求解优化。首先,采用一种新的编码思想构建双层染色体编码结构,强化初始种群质量,提高种群的多样性;并给出相应的选择操作设计,交叉操作采用单段交叉、两段交叉和三段交叉机制,改善算法全局搜索能力,变异操作引入种群分割的思想,按照适应度将种群分割成两部分,并赋予不同的变异概率,实行两种变异机制,以提高算法的局部搜索能力;添加新的检查操作以增强优化过程的可行性。最后采用MATLAB编程,通过一个6个工件、每工件6道工序的应用实例进行测试,验证了该方法切实可行有效。

Aiming at the traditional job shop scheduling problem,such as the function monotony and the fixed collocation of processing equipment,an improved genetic algorithm was proposed.First,a new coding idea was used to construct a two-layer chromosome coding structure,with which the initial population quality was strengthened and the diversity of the population improved.The corresponding selection operation design was given,and single-segment,double-segment,and triple-segment crossovers were used for cross operation.The crossover mechanism improved the global search ability of the algorithm.The idea of population segmentation was introduced into the mutation operation.The population was divided into two parts according to the fitness,and different mutation probabilities were assigned.Two mutation mechanisms were implemented to improve the local search ability of the algorithm.New inspection operations were added to enhance the feasibility of the optimization process.Finally,MATLAB programming was used to test an application example of 6 workpieces and 6 working procedures per each workpiece.The results verify that the method is feasible and effective.