基于改进粒子群算法的设备维修调度优化研究

Study on Optimization of Equipment Maintenance Scheduling Based on Modified Particle Swarm Optimization Algorithm

为保障离散制造企业生产系统的连续性并降低其维修成本,构建了以维修时间最短和维修成本最低为目标的设备维修调度优化模型,并采用改进粒子群算法对模型进行求解。针对标准粒子群算法后期易陷入局部最优的缺点,采用指数函数递减的惯性权重形式来平衡算法的全局搜寻能力和局部搜寻能力,在速度更新公式和位置更新公式中分别引入速度扰动项和飞行时间因子以提高算法的收敛能力。以某机械公司生产车间设备维修调度为例,验证了该方法的有效性和适应性。

To ensure the continuity and reduce the maintenance cost of production system of discrete manufacturing enterprises,an equipment maintenance scheduling optimization model was built for minimizing maintenance time and maintenance cost,and the model was solved with modified particle swarm optimization algorithm.Considering the defect that it is liable to fall into local optimum with the particle swarm optimization algorithm in the later iteration,the discending inertia weight of exponential function was adopted for balancing the global search capability and local search capability of the algorithm,and velocity perturbation and flying time factor were introduced into the velocity updating formula and the location updating formula respectively to improve the convergence ability of the algorithm. The effectiveness and adaptability of the method have been proved via case study of equipment maintenance scheduling of production workshop of a machinery company.