改进人工免疫算法求解柔性作业车间调度问题

Flexible Job-shop Scheduling Problem Solved by Improved Artificial Immune Algorithm

柔性作业车间的合理调度是提高生产效率和效益的关键,为了解决柔性作业车间调度问题求解过程中的难题,提出一种改进人工免疫算法的柔性作业车间调度方法.首先对当前柔性作业车间调度的研究现状进行分析,然后基于总加工时间最短构建数学模型,采用人工免疫算法进行求解,并针对标准人工免疫算法存在的不足,引入粒子群算法保持种群的多样性,以避免出现局部最优解,最后采用标准算例集对算法的性能进行仿真测试.结果表明,相对于其他算法,改进人工免疫算法获得了较优的柔性作业车间调度方案,尤其在解决大规模问题时,优势更加显著.

A novel flexible job shop scheduling method based on improved artificial immune algorithm was proposed. Mathematical model of the flexible job shop scheduling was established, and the total shortest processing time was taken as the objective function. The particle swarm optimization algorithm as the oper- ator was embedded into artificial immune algorithm to maintain the diversity of population and prevent ob- taining local optimal solution. The performance of the algorithm was tested by simulation experiments on standard set. Results showed that compared with other algorithms, the proposed algorithm could obtain better flexible job shop scheduling scheme, especially large-scale problems.