陈丽, 黄晋. 基于空间索引的物流中心选址方法[J]. 华南师范大学学报(自然科学版), 2016, 48(4): 113-118. doi: 10.6054/j.jscnun.2015.12.012
引用本文: 陈丽, 黄晋. 基于空间索引的物流中心选址方法[J]. 华南师范大学学报(自然科学版), 2016, 48(4): 113-118. doi: 10.6054/j.jscnun.2015.12.012
CHEN Li, HUANG Jin. A Selection Method Based on Spatial Index for Logistics Center Location[J]. Journal of South China Normal University (Natural Science Edition), 2016, 48(4): 113-118. doi: 10.6054/j.jscnun.2015.12.012
Citation: CHEN Li, HUANG Jin. A Selection Method Based on Spatial Index for Logistics Center Location[J]. Journal of South China Normal University (Natural Science Edition), 2016, 48(4): 113-118. doi: 10.6054/j.jscnun.2015.12.012

基于空间索引的物流中心选址方法

A Selection Method Based on Spatial Index for Logistics Center Location

  • 摘要: 确定合理的城市物流节点位置,对优化物流网络、提高物流服务水平、改善城市交通状况都具有十分重要的作用. 文中提出了一种实用新型的选址查询方法,在已知人口分布和已建物流中心位置的基础上,从候选位置集中返回前k个最具有影响的位置,作为待建物流中心的参考,这种查询在决策支持系统中有广泛的应用. 该算法利用R-tree为3个已知位置集进行了索引,并提出基于候选位置影响力的排序方法,以此制定了有效的剪枝规则,大大减少了搜索复杂度. 实验表明,该算法具有很好的查询效率.

     

    Abstract: To determine reasonable locations for logistics nodes will be helpful for optimizing logistics network, improving logistics services and alleviating urban traffic conditions. A novel and practical location query is proposed, that is, given population distribution and existing logistics nodes, it is to retrieve the Top-k most influential locations from a candidate set, which can be taken as candidate locations for new logistics nodes. This new query type will be widely used in decision support system. R-tree indexes are built for the three location sets and ranking method are presented for candidate locations importance. Furthermore, three effective pruning rules are addressed to reduce the search complexity dramatically. Experiments demonstrate that the presented algorithm has good query efficiency and the pruning strategies are very effective.

     

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