Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making
Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making
复制标题
随机需求下的公共交通枢纽选址：一种基于多属性群决策的改进方法
DOI：
10.1155/2015/430109
复制
发表时间：
2015-12
影响因子：
1.4
通讯作者：
Zhong Shuqi
中科院分区：
文献类型：
--
作者：
Liu Sen;Song Zhilan;Zhong Shuqi
城市公共交通枢纽是公共交通系统的关键节点。此类枢纽的位置是一个组合问题。影响选址决策的因素很多，包括定量因素和定性因素；然而，当前大多数研究仅关注定量或定性因素。很少有人将这两种方法结合起来。为了弥补研究中的这一空白，本文提出了一种考虑定量和定性因素的公共交通枢纽选址问题的新方法。本文提出一种基于TOPSIS（理想解相似顺序偏好技术）和偏差的改进多属性群决策（MAGDM）方法，将各枢纽的定性因素转化为定量评价值。然后根据上述评价值建立随机客流的选址模型。最后应用随机规划理论对模型进行求解并确定定位结果。数值研究表明该方法是适用且有效的。
Urban public transportation hubs are the key nodes of the public transportation system. The location of such hubs is a combinatorial problem. Many factors can affect the decision-making of location, including both quantitative and qualitative factors; however, most current research focuses solely on either the quantitative or the qualitative factors. Little has been done to combine these two approaches. To fulfill this gap in the research, this paper proposes a novel approach to the public transportation hub location problem, which takes both quantitative and qualitative factors into account. In this paper, an improved multiple attribute group decision-making (MAGDM) method based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and deviation is proposed to convert the qualitative factors of each hub into quantitative evaluation values. A location model with stochastic passenger flows is then established based on the above evaluation values. Finally, stochastic programming theory is applied to solve the model and to determine the location result. A numerical study shows that this approach is applicable and effective.
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影响因子：
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作者：
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通讯作者：
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DOI：
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