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基于GIS-AHP的建筑废弃物消纳场选址优化研究——以广州市番禺区为例 被引量:3

Optimization of the Construction and Demolition Waste Recycling Facilities Location Based on GIS-AHP:A Case Study of Panyu District,Guangzhou City
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摘要 随着我国城市化进程的加快,新建建筑和拆迁改造项目产生了巨量废弃物。如果建筑废弃物消纳场场址选择不当,就会对环境、社会和经济造成重大的影响。为此,结合AHP-Entropy方法,利用GIS技术,使用整数规划建立建筑废弃物物流回收网络,以广州市番禺区为例,构建选址优化模型,确定了番禺区内最适宜建设消纳场的位置。综合考虑了与消纳场建设和运营有关的各项成本,确定了消纳场的理想数量和建议容量。建筑废弃物消纳场属于邻避型设施,因此建设时要考虑当地居民对建设消纳场影响,研究结果可以为政府管理部门规划建筑废弃物物流管理链,以及为消纳场选址等方面提供参考。 With the acceleration of urbanization process of China,new buildings,demolition and renovation projects generated huge amount of waste.If the site of the construction and demolition waste(C&DW)recycling facilities is not properly selected,it will cause great impacts on the environment,society and economy.This study,therefore,applies the GIS technology in combination with the AHP-Entropy method to establish a C&DW recycling network based on integer programming.This study takes Panyu District of Guangzhou as an example and constructs a location optimization model.It determines the most suitable location of C&DW recycling facilities site in Panyu district.The ideal quantity and recommended capacity of the C&DW recycling facilities are determined by comprehensively considering various costs related to the construction and operation of the C&DW recycling facilities.Due to the C&DW recycling facility is a kind of NIMBY(Not In My Back Yard)facilities,construction must pay attention to the influences of waste recycling facilities site to residents.The research results can provide references for the government to select the most appropriate site for C&DW recycling facilities,and to plan C&DW logistics management chain.
作者 刘景矿 马冲 LIU Jing-kuang;MA Chong(School of Management,Guangzhou University,Guangzhou 510006,China)
出处 《工程管理学报》 2020年第4期74-79,共6页 Journal of Engineering Management
基金 国家自然科学基金青年科学基金项目(71501052) 教育部人文社科研究青年项目(20YJCZH097) 广东省哲学社会科学规划项目(GD19CGL23) 广州市哲学社科规划课题(2020GZGJ185)。
关键词 建筑废弃物消纳场 AHP-Entropy 选址优化 整数规划 C&DW recycling facilities AHP-Entropy location optimization integer programming
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