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| Seismic resilience assessment of power supply system based on multi-level adaptive cooperative algorithm |
Xiaohang LIU1( ),Qing QIN1,*(),Kaige WANG2,Jun HUANG2,Changyou WANG2 |
1. School of Civil and Architectural Engineering, Xi’an University of Science and Technology, Xi’an 710055, China
2. School of Civil Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China |
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Abstract A multi-objective optimization–based multi-dimensional assessment and decision-making method for seismic resilience was proposed in order to quantitatively assess and enhance the seismic resilience and recovery efficiency of urban power supply system. Performance functions and resilience indicators were constructed from three dimensions—technical, organizational, and social—to quantitatively characterize the post-earthquake functional degradation and recovery process of the system. A multi-level adaptive cooperative algorithm (MACA) was introduced. Graph-theory-based partition heuristic encoding, hierarchical Pareto clustering, and dynamic learning rates were employed to improve convergence stability and global search capability while preserving solution diversity. Information synergy and experience transfer among repair groups were realized through node partitioning and dynamic allocation of repair crews, ultimately yielding a comprehensive optimal restoration plan. Case study results demonstrate that the three-dimensional framework can effectively quantify post-earthquake performance and reveal the differential recovery across dimensions. The MACA-optimized scheme improved organizational and social resilience by 5.2% and 3.7%, respectively compared with random restoration. The algorithm achieved a convergence rate of 98.9%, and the variance of the solution set was reduced by 46.7% compared with NSGA-Ⅱ.
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Received: 23 October 2025
Published: 21 October 2026
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| Fund: 陕西省科技厅资助项目（2025JC-YBQN 529）；陕西省教育厅专项科研计划资助项目（25JK0550）. |
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Corresponding Authors:
Qing QIN
E-mail: liuxiaohang@xust.edu.cn;qinqing@xust.edu.cn
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基于多层次自适应协同算法的供电系统抗震韧性评估
为了量化评估并提升城市供电系统的抗震韧性与恢复效率，提出多目标优化的抗震韧性多维度评估与决策方法. 从技术、组织、社会3个维度构建性能函数与韧性指标，量化表征系统震后功能退化与恢复进程. 提出多层次自适应协同算法（MACA），采用图论分区启发式编码、层次化帕累托聚类与动态学习率，在保持解集多样性的同时提升收敛稳定性与全局寻优能力. 算法通过节点分区与修复队伍动态分配，实现修复群体间信息协同与经验迁移，获得综合最优修复方案. 算例结果表明，三维度框架能够有效量化震后性能并揭示各维度恢复差异；MACA优化方案相较随机修复，组织维度与社会维度的恢复力分别提升了5.2%和3.7%. 算法收敛率达到98.9%，解集方差较NSGA-Ⅱ降低了46.7%.
关键词：
多目标优化,
自适应协同优化算法,
供电系统,
抗震韧性,
三维度评估
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