摘要
为了能够准确反映信息传播对于应急物资需求的影响以及有效优化应急配送车辆的路径,构建了基于双层扩散网络的需求预测模型和改进的离散人工蜂群算法(进化蜂群算法)。首先,在分析扩散网络中事件层和信息层关系的基础上构建了物资需求预测模型。其次,在进化蜂群算法中,依据适应度值和历史进化程度来甄别优秀信息,并融合了交叉算子和变异算子使蜜源得以不断进化,从而充分挖掘了蜂群价值并有效提升了迭代效率。仿真实验结果表明,应急物资得以被短时高效地配送到所需区域,从而验证了所构建的模型和算法能够有效求解信息传播影响下的应急车辆路径多目标优化问题。
In order to accurately reflect the impact of information dissemination on material requirements and to effectively optimize the route of distribution vehicles,a demand prediction model based on the two-layer spread network and an improved discrete artificial bee colony algorithm(evolutionary bee colony algorithm)were constructed.Firstly,based on the analysis of the relationship between the event layer and the information layer in the spread network,a material demand prediction model was established.Then,by the evolutionary bee colony algorithm,good information was screened according to fitness value and historical evolutionary,and the crossover operator and mutation operator were integrated to make honey sources continuously evolve,so as to fully extract the colony value and effectively improve the iterative efficiency.The simulation experiment results show that emergency supplies can be efficiently delivered to the required areas in a short time,thus verifying that the proposed model and algorithm can effectively solve the multi-objective optimization problem of the emergency vehicle route design under the influence of information dissemination.
作者
于明亮
刘帅
浦东平
YU Mingliang;LIU Shuai;PU Dongping(Public Experiment Center,University of Shanghai for Science and Technology,Shanghai 200093,China;College of Information,Mechanical and Electrical Engineering,Shanghai Normal University,Shanghai 200234,China)
出处
《上海理工大学学报》
CAS
CSCD
北大核心
2021年第1期83-92,共10页
Journal of University of Shanghai For Science and Technology
关键词
应急物流
信息传播
蜂群算法
车辆路径问题
多目标优化
emergency logistics
information dissemination
bee colony algorithm
vehicle routing problem
multi-objective optimization
