综合考虑服务水平和资源占用的平行机调度问题

【目的】对综合考虑服务水平和资源占用的平行机调度问题进行研究，建立以最小化总延误和机器使用数量之和为优化目标的优化模型。【方法】针对该问题的特点，设计了一种改进的模拟退火算法进行求解。采用不同规模的数值实验测试算法的性能，并对问题参数展开灵敏度分析。【结果】改进的模拟退火算法具有良好的求解效率和求解质量。【结论】灵敏度分析表明，增加资源储备可以使企业更好地平衡服务水平和资源占用。模型能够对企业实现资源节约型制造提供指导和决策支持。

Parallel Machine Scheduling Problem Concerned with Service Level and Resource Consumption

Purposes] Improved dynamic line loss and sparse optimization methods are used to study the operation error estimation of smart meters. Methods] First, considering the sparsity of meter error, the sparse regular term is added to improve the dynamic line loss model and improve the accuracy of error estimation. Furthermore, ADMM algorithm is used to improve the design iteration algorithm, and the dynamic line loss model is solved alternately to obtain the error estimation results of smart meters. Findings] The numerical simulation experiment is performed by using MATLAB and actual data to verify the effectiveness of the proposed method. Conclusions] The results show that the coupling relationship between line loss rate and measurement error estimation is analyzed, and the accuracy of error estimation is improved. Compared with the dynamic line loss model, the detection accuracy of the proposed method is better.