摘要
"小城镇,大战略"背景下,加强小城镇应急管理成为一项具有重大挑战性的研究课题。针对我国小城镇应急设施选址定量分析文献较少的现实,结合小城镇应急物资储备库管理与物资调度实际,对等级设施选址理论中的最大覆盖模型加以改进,构建了考虑覆盖半径内需求满意差异性,具有单流、嵌套性、同调性特征的小城镇应急物资储备库等级选址模型,并利用蚁群算法进行求解。以北京房山区为例进行实证,以整体应急服务满意度最大为目标,实现了房山区8个区级应急物资储备库、25个乡镇级应急物资储备库的等级优化配置,并绘出配置图,给出房山区应急物资储备库优化配置的相关建议,为我国小城镇应急管理工作的科学化提供一定的决策依据。
According to the deployment of "Small town,grand strategy",urbanization of China has entered a key stage. However,it is confronted with a great challenge for China to strengthen emergency management of small town. Emergency management for small town needs a resource allocation system with flexibility,fluency,punctuality,rationality and effectiveness. Based on the plan of Beijing government,every town in Beijing will establish one emergency material depository before 2020. There are few documents analyzing the allocation of small-town emergency material depository of China with quantitative methods. Also,the traditional facility location problems think little of the satisfaction difference between demand points in the covering radius of facility. In the light of this situation,we present a hierarchical maximal covering location problem considering the demand satisfaction difference between demand points in the domain of facility covering radius and formulate a maximal covering model as an integer programming under the goal of maximizing the total satisfaction of demand points. After investigating the characteristics of the model formulated,we introduce super-node algorithm to solve the considered problems. Then,we get the allocation result of emergency material depository of Fangshan District in Beijing. The computational result have shown that the model we proposed generate facility location solutions in a more effective manner. Finally,we also propose extensions to our research.
出处
《灾害学》
CSCD
2016年第2期156-163,共8页
Journal of Catastrophology
基金
国家社会科学基金项目(13BGL130)
2014年河北省高等学校青年拔尖人才计划项目(BJ201409)
关键词
设施选址
应急物资储备库
等级最大覆盖
小城镇
北京市房山区
facility location
emergency material depository
hierarchical maximal covering
small town
Fangshan District of Beijing