摘要
自然灾害和突发事件会对社会经济造成巨大损失,应急物资对于突发事件的救援是必须的,应急物资调运是应急物流的核心问题。因此,应用灰狼优化算法设计一种新的应急物资供应点选择方法。划分灰狼群体等级,明确应急物资调配过程。以供应时间最短与供应成本最低为目标,构建应急物资供应点选择的目标函数。基于非线性过度参数综合分析应急物资供应点的供应成本和供应时间,求解相似接近度,将相似接近度从大到小排列,选择应急物资最佳供应点。实验结果表明,所提方法具有良好的寻优能力,能够有效提高收敛精度和速度,在进行供应时,具有较高的适应度。
Natural disasters and emergencies can cause huge losses to the social economy,and emergency supplies are necessary for the rescue of emergencies.The transportation of emergency materials is the core issue of emergency logistics.Thus,this paper applies the grey wolf optimization algorithm to design a new method for selecting emergency material supply point.This paper classifies the gray wolf population and clarifies the process of emergency material allocation,constructs an objective function for selecting emergency material supply point with the goal of minimizing supply time and supply cost.Based on the comprehensive analysis of nonlinear transition parameters,the supply cost and supply time of emergency material supply point are analyzed,the similarity degree is solved,and the similarity degree is arranged from highest to lowest to select the optimal supply point for emergency material.The experimental results show that the proposed method has good robustness,can effectively improve the convergence accuracy and speed,and has a high fitness when supplying.
作者
吴跃
张静鑫
焦飞
WU Yue;ZHANG Jingxin;JIAO Fei(Information and Communication Branch of State Grid Anhui Electric Power Co.,Ltd.,Hefei 230022,China;Anhui Mingsheng Hengzhuo Technology Co.,Ltd.,Hefei 230031,China)
出处
《微型电脑应用》
2025年第3期196-199,共4页
Microcomputer Applications
关键词
灰狼优化算法
应急物资
供应点选择
最短供应时间
供应成本
grey wolf optimization algorithm
emergency material
selection of supply point
minimum supply time
supply cost
作者简介
吴跃(1990-),男,硕士,工程师,研究方向为电力信息系统及其自动化;张静鑫(1978-),男,本科,助理工程师,研究方向为机器学习、人工智能、大数据;焦飞(1985-),男,本科,高级工程师,研究方向为人工智能、数据分析、区块链。
