基于元胞遗传算法的多目标应急资源配置  

Multi-objective emergency resource distribution based on cellular genetic algorithm

作　　者：王飞跃[1] 裴重伟 郭换换 杨宸宇 WANG Feiyue;PEI Chongwei;GUO Huanhuan;YANG Chenyu(Institute of Disaster Prevention Science and Safety Technology,Central South University,Changsha Hunan 410075,China)

机构地区：[1]中南大学防灾科学与安全技术研究所

出　　处：《中国安全生产科学技术》2020年第2期174-179,共6页Journal of Safety Science and Technology

基　　金：湖南省2017年度安全生产专项资金项目(201720)

摘　　要：为解决不同灾情下多目标多周期灾后救援问题,减少受灾损失,对灾后应急资源配置进行研究。从物流成本和系统损失2个方面最小化救灾行动的成本和最大化有限救灾资源的分配,建立基于路况的多目标应急资源配置模型,将帕累托前沿和超体积作为元胞遗传算法的求解性能指标,开展元胞遗传算法与遗传算法对模型的求解对比实验。结果表明:元胞遗传算法能较好地求解多目标多周期应急资源配置模型,且求解性能比遗传算法更好;通过对模型的求解,可为决策者基于不同灾情下的应急决策提供参考。In order to solve the problem of multi-objective and multi-period post-disaster rescue under different disaster situation,and mitigate the disaster losses,the post-disaster emergency resource distribution was studied.A multi-objective emergency resource distribution model based on the road conditions was established to minimize the cost of disaster rescue operation and maximize the distribution of limited disaster rescue resource from two aspects of logistics cost and system losses.The solving and comparison experiments of the model with the cellular genetic algorithm and genetic algorithm were carried out by taking the Pareto front and hypervolume as the solving performance indexes of cellular genetic algorithm.The results showed that the cellular genetic algorithm could solve the multi-objective and multi-period emergency resource distribution model well,and the solving performance was better than that of genetic algorithm.Through the solving of the model,it can provide reference for the emergency decision-making of decision-makers under different disaster situation.

关 键 词：应急资源配置 元胞遗传算法 多目标优化 

分 类 号：X913.4[环境科学与工程—安全科学]