自动化仪表检测中的车间调度问题优化与仿真

Optimization and simulation of job shop scheduling problem in automatic instrument test

为解决自动化仪表检测工作中的作业车间调度问题以提高其工作效率,提出一种基于生命力选择的精英鲸鱼优化算法。利用生命力选择方法替换表现较差的个体,克服鲸鱼优化算法在调节搜索范围方面的不足,避免种群陷入局部最优,加快种群向全局最优解收敛的速度。结合标准实例和北京东方计量测试研究所的自动化仪表检测实例,对算法进行仿真分析,验证了精英鲸鱼优化算法在求解作业车间调度问题的有效性和稳定性,其可以满足自动化仪表检测工作中的日常检测任务调度需求。

To solve the job shop scheduling problem in automatic instrument test and improve its efficiency,an elite whale optimization algorithm(EWOA)based on vitality selection was proposed.The poor performance individuals were replaced using vitality selection.The problem of adjusting search scope of whale optimization algorithm was effectively addressed,and populations were prevented from falling into local optima and the population convergence was accelerated to global optimal solution.The simulation experiments were carried out in standard test problems and the automatic-instrument-test problems in Beijing Orient Institute of Measurement and Test.The simulation results indicate that EWOA has better effectiveness and robustness,which demonstrates that it is able to satisfy the real scheduling requirements in automatic instrument test.