基于改进的PSO算法,优化电网材料仓储和供应链分销路径规划
Junping Ge1, Tao Wang2, Kairui Hu3
1Jinhua Power Supply Company, State Grid Zhejiang Electric Power Co., Ltd., Jinhua, 321000, China. ejhgjp@126.com.
Scientific reports
|December 22, 2025
概括
本研究介绍了智能电网应急物流的先进优化模型,提高了材料分类的准确性,并大大减少了灾害期间的交付时间. 该模型在复杂的供应链场景中提高了效率和适应性.
科学领域:
- 工程 工程师 工程师 工程师
- 计算机科学 计算机科学
- 运营研究 运营研究
背景情况:
- 智能电网建设增加了电网材料仓储和紧急分配的复杂性.
- 传统方法在动态灾害场景中难以提高搜索效率和适应性.
研究的目的:
- 开发一个高效和可扩展的优化模型,用于智能电网材料管理和紧急分配.
- 解决传统方法在搜索效率和动态场景适应性方面的局限性.
主要方法:
- 整合了多策略协作自适应的混乱粒子群优化算法和改进的帝国主义竞争算法.
- 纳入多策略混乱干扰和适应性惯性权重,以优化库存参数.
- 实施鱼骨仓库布局,免疫惩罚校正和激素自适应平衡,以加强采摘和路径规划.
主要成果:
- 在材料分类中获得了98.73%的准确性.
- 在地震场景中,交付时间从6.78小时缩短到4.56小时.
- 证明了供应链分销路径解决方案的0.45s单次代计算时间,结合了稳定性和效率.
结论:
- 拟议的模型在多目标优化,仓库布局规划和紧急物流路径安排方面提供了显著的优势.
- 为智能电网材料管理和紧急分配提供可行的技术解决方案.
- 为复杂的供应链优化研究提供了新的方法参考.
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