改进的SAGA算法在变电站巡检作业调度中的应用

针对多资源约束条件下变电站巡检作业调度问题,根据巡检成员的位置、当前任务、任务详情、待执行任务、巡检设备、设备历史巡检记录等因素，构建数学模型，并在此模型基础上提出一种改进的遗传算法。该算法解决了传统遗传算法陷入局部最优解的问题，且具有收敛速度快的特点。实验结果表明，SAGA算法在解决变电站巡检作业调度问题方面要优于GA算法，且具有更高的求解效率。 

Application of Improved SAGA Algorithm in Substation Inspection Job Scheduling

Against the substation inspection operation scheduling problem under the condition of multi-resource constraints, according to the location of the inspection members, the current mission, the mission details, the tasks to be implemented, inspection equipment, historical inspection records and other factors, we built a mathematical model, and put forward an improved genetic algorithm. The algorithm solves the problem that the traditional genetic algorithm falls into the local optimal solution, and has the characteristics of fast convergence speed. The experimental results show that the SAGA algorithm is superior to GA algorithm to solve substation inspection job scheduling problem, and has higher calculation efficiency. 