摘要
针对决策者在短时间内选择救援队伍与路径的复杂挑战,研究应急物资供应中的路径规划问题,提出一种结合层次分析法(analytic hierarchy process,AHP)与Dijkstra算法的成本效应路径规划模型。首先,通过AHP方法对应急情景中的多类准则进行系统化量化排序,确定各因素权重;其次,综合考虑物资分布地理坐标与突发事件信息,构建融合多源数据的风险成本图模型,运用改进DIJKSTRA算法迭代生成总风险成本最低的救援路径;最后,通过仿真实验对比不同路径在风险成本与计算时间方面的表现。实验结果验证了模型在动态应急环境中的可行性与有效性,能够在保证计算效率的同时显著降低路径风险成本,为应急资源调度与路径优选提供了一种科学、实用的决策支持工具。
This paper focuses on the path planning problem in emergency material supply.In response to the complex challenges faced by decision-makers in selecting rescue teams and routes within a short period of time,a cost-effectiveness path planning model combining the analytic hierarchy process(AHP)and Dijkstra algorithm is proposed.Firstly,using the AHP method,the various criteria in the emergency scenario are systematically quantitatively ranked to determine the weights of each factor.Secondly,considering the geographical coordinates of material distribution and emergency event information,a risk cost graph model integrating multiple data sources is constructed,and the improved Dijkstra algorithm is used to iteratively generate the rescue path with the lowest total risk cost.Finally,through simulation experiments,the performance of different paths in terms of risk cost and calculation time is compared.The results verify the feasibility and effectiveness of the model in dynamic emergency environments,and can significantly reduce the path risk cost while ensuring computational efficiency,providing a scientific and practical decision support tool for emergency resource scheduling and path optimization.
作者
张新菊
ZHANG Xinju(Emergency Management Department Big Data Center,Beijing 100013,China)
出处
《自动化技术与应用》
2026年第4期78-82,121,共6页
Techniques of Automation and Applications
基金
科技创新2030—“新一代人工智能”重大项目(2021ZD0114200)。
