摘要
为充分利用应急物资和提高应急响应能力,考虑灾害初期道路通行受约束和运输能力受限等因素,建立最小化受灾点平均等待救援时间和最小化应急物资调度成本的多目标优化模型。采用基于自适应机制的NSGA-II算法,引入种群熵和高斯函数,动态调整变异、交叉概率,将变异、交叉过程与进化的横向和纵向信息相结合,以引导种群的进化,提高进化速度;为充分探索解空间,设计了基于贪婪思想的随机变邻域搜索算子,并使用替换策略,消除Pareto前沿中相同解对进化带来的负面影响。通过算例对所提算法进行验证,结果表明:所提改进算法优于传统NSGA-II算法和已知文献算法,能在保持较好收敛性的同时获得更好的多样性。
In order to make full use of emergency supplies and improve emergency response capacity,a multi-objective optimization model was established to minimize the average waiting time of disaster sites and the dispatching cost of emergency supplies,taking into account the constraints of road passage and transportation capacity in the initial stage of disaster.Population entropy and Gaussian function were introduced by the improved NSGA-II,based on adaptive mechanism,to dynamically adjust mutation and crossover probability,and combined mutation and crossover process with horizontal and vertical information of evolution to guide population evolution and improve evolution speed.A random variable neighborhood search operator based on greedy idea was designed to fully explore the solution space.The influence of the same on evolution in Pareto frontier was eliminated by adjusting the strategy.An example was given to verify the proposed algorithm,and the results shown that the proposed algorithm was superior to the traditional NSGA-II algorithm and the known literature algorithm,and maintained good convergence and obtained better diversity.
作者
王付宇
张康
WANG Fuyu;ZHANG Kang(School of Management Science and Engineering,Anhui University of Technology,Maanshan 243002,China;Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes, Anhui University of Technology, Maanshan 243002, China)
出处
《复杂系统与复杂性科学》
CAS
CSCD
北大核心
2022年第2期53-62,共10页
Complex Systems and Complexity Science
基金
安徽省哲学社会科学规划项目(AHSKY2018D15)。
关键词
应急物资调度
多式联运
自适应机制
多目标优化
智能优化算法
emergency supplies scheduling
multimodal transport
adaptive mechanisms
multi-objective optimization
intelligent optimization algorithm
