基于遗传蚁群算法的变电站优先维护规划

Ruijia Ma, Yanjia Luo, Ke-Fan Xie, Peng Li, Jie Wu
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引用次数: 0

摘要

在变电站的处理中,合理安排各变电站维修使用的路线是非常关键的。此外,鉴于不同变电站的紧急程度,应仔细考虑各变电站的优先级,以便安排好维修所用的路线。本文考虑到路由安排的复杂性,采用遗传算法(GA)和蚁群算法(ACO)结合设计的优先级编码方法和优先级约束,使路由安排更加合理。此外,通过分析遗传算法和蚁群算法在基于优先级的路由安排上的性能,设计了一种融合算法,以高效地获得较好的路由安排。实验结果表明,在设计的优先级编码方法和优先级约束条件下,基于融合的方法可以获得更合理的结果。
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Substation priority maintenance planning based on genetic ant colony algorithm
In the treatment of substations, it is very crucial to make a reasonable arrangement of route used for the maintenance of each substation. Moreover, given the urgency degree of different substations, the priority of each substation should be carefully considered for a good arrangement of route used for the maintenance. In this paper, considering the complexity of the routing arrangement, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) were adopted with the designed priority coding methods and priority constraints for a more reasonable arrangement of route. Moreover, with the analysis of the performances of GA and ACO on the priority-based routing arrangement, a fused method was designed to obtain a good routing arrangement in an efficient manner. The experimental results show that, with the designed priority coding method and the priority constraints, a more reason result can be obtained by the fusion-based method.
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