地理研究

地理研究 ›› 2011, Vol. 30 ›› Issue (6): 1000-1008.doi: 10.11821/yj2011060004

• 经济与区域发展 • 上一篇    下一篇

基于选址理论的小城镇应急物资储备库优化配置——以北京房山区为例

陆相林1,2, 侯云先1, 林文3, 申强1   

  1. 1. 中国农业大学经济管理学院,北京 100083;
    2. 枣庄学院旅游与资源环境系,山东枣庄 277160;
    3. 中国地质大学人文经管学院,北京 100083
  • 收稿日期:2010-07-12 修回日期:2010-09-25 出版日期:2011-06-20 发布日期:2011-06-20
  • 通讯作者: 侯云先(1965-),女,河南郑州人,教授,博士生导师,研究方向为物流与供应链管理、应急管理。E-mail:houyunxian@163.com
  • 作者简介:陆相林(1977-),男,汉族,河南台前人,讲师,博士生,研究方向为管理系统优化与物流管理。 E-mail:luxianglin1@sohu.com
  • 基金资助:

    "十一五"国家科技支撑重点项目课题(2006BAJ07B08、2006BAJ07B09);中国农业大学2010年研究生科研创新专项基金

Allocation of small-town emergency material depository based on location theory: A case study of Fangshan District in Beijing

LU Xiang-lin1,2, HOU Yun-xian1, LIN Wen3, SHEN Qiang1   

  1. 1. College of Economics and Management, China Agricultural University, Beijing 100083, China;
    2. Department of Tourism and Resource Environment of Zaozhuang University, Zaozhuang 277160, Shandong, China;
    3. School of Humanities and Economic Management, China University of Geosciences, Beijing 100083, China
  • Received:2010-07-12 Revised:2010-09-25 Online:2011-06-20 Published:2011-06-20

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摘要： 按照"小城镇,大战略"的部署,我国已进入城镇化发展的关键时期。加强小城镇突发公共事件的应急管理,建立符合我国国情尤其是农村农情的应急管理模式,成为一项重大的挑战性的研究课题。针对我国小城镇应急物资储备库选址合理性定量分析研究较少的现实,基于选址理论中的最大覆盖模型原理,考虑了覆盖半径内的需求满意差异问题,构建了覆盖半径内需求满意存在差异的最大覆盖设施选址模型,并提出利用蚁群算法进行求解。以北京房山区为例对模型和算法进行实证,得出设8个应急物资储备库时的归属单位,服务乡(镇)与服务半径,并给出配置图。最后,提出了进一步拓展研究的方向。

关键词: 选址, 小城镇, 最大覆盖, 应急物资储备库

Abstract: Urbanization has entered a key stage in China. Since the implementation of the policy of "small town, grand strategy", small towns have played a critical role in China's urbanization. However, China is one of the countries that have suffered various natural disasters, and is fighting against technological accidents as well as more terrorist attacks and criminal activities. China is confronted with a great challenge to strengthen the emergency management for small towns, so it seeks for a resource allocation system with flexibility, fluency, punctuality, rationality and effectiveness. The Chinese Government is therefore striving to intensify the emergency management system. For instance, according to the plan of Beijing government, every big community or neighborhood in Beijing will establish one to two emergency material depositories in the coming 3 to 5 years. So far there have been relatively few documents on the allocation of small-town emergency material depository with quantitative methods. Besides, the location of traditional facilities seldom focused on the satisfaction difference of demand points within the covering radius of facilities. In the light of this situation, we present a maximal covering location and build a maximal covering model as an integrated programming under the goal of maximizing the total satisfaction of demand points. After investigating the model, we introduced an ant colony optimization (ACO) algorithm to solve the considered problems. Then, we obtained the allocation result of emergency material depository of Fangshan District in Beijing. The computed results have shown that the model we proposed is a solution to facility location in a more effective manner. Finally, we give suggestions to future research.

Key words: location, small-town, maximal covering, emergency material depository