Inequality measures and equitable locations
Inequality measures and equitable locations
复制标题
不平等措施和公平地点
DOI：
10.1007/s10479-007-0234-9
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发表时间：
2009
影响因子：
4.8
通讯作者：
W. Ogryczak
中科院分区：
文献类型：
--
作者：
W. Ogryczak
摘要
在进行选址决策时，服务接受者（客户）之间的距离（结果）分布是一个重要问题。为了遵守最小化距离以及平等考虑客户，通常使用平均公平方法。他们以两个标准的清晰形式量化问题：代表整体效率的平均结果和代表公平（公平）方面的结果不平等的标量度量。均值-公平模型对决策者很有吸引力，可以进行简单的权衡分析。另一方面，对于典型的分散指数作为不平等的措施，平均公平的方法可能会导致劣质的结论与距离最小化。然而，一些不等式度量可以与平均值本身组合成优化标准，这些标准与不等式最小化和距离最小化保持一致。在本文中，我们介绍了一般条件的不平等措施足以提供这样一个公平的一致性。我们验证了基本的不平等措施的条件，从而显示它们如何可以用于位置模型，而不会导致劣质分布的距离。
Abstract
While making location decisions, the distribution of distances (outcomes) among the service recipients (clients) is an important issue. In order to comply with the minimization of distances as well as with an equal consideration of the clients, mean-equity approaches are commonly used. They quantify the problem in a lucid form of two criteria: the mean outcome representing the overall efficiency and a scalar measure of inequality of outcomes to represent the equity (fairness) aspects. The mean-equity model is appealing to decision makers and allows a simple trade-off analysis. On the other hand, for typical dispersion indices used as inequality measures, the mean-equity approach may lead to inferior conclusions with respect to the distances minimization. Some inequality measures, however, can be combined with the mean itself into optimization criteria that remain in harmony with both inequality minimization and minimization of distances. In this paper we introduce general conditions for inequality measures sufficient to provide such an equitable consistency. We verify the conditions for the basic inequality measures thus showing how they can be used in location models not leading to inferior distributions of distances.
DOI：
10.1016/b978-0-12-557189-0.x5000-8
发表时间：
2004
期刊：
--
影响因子：
--
作者：
M. Pióro;D. Medhi
通讯作者：
M. Pióro;D. Medhi