摘要翻译：
我们提出了一个新的顶狗指数来量化一个商品组的许多小分支的供应数据与销售数据的历史偏差。一方面，文献中关于客户需求分布的常见参数假设在我们的现实数据集中根本不支持。另一方面，一种合理的非参数方法直接从销售分布估计不同部门的需求分布，只能为我们提供统计上微弱和不可靠的未来需求估计。基于我们的行业合作伙伴的真实销售数据，我们提供了证据，证明我们的顶级狗指数在统计上是稳健的。利用top-dog指数，我们提出了一个启发式算法来提高供应和需求之间的分支依赖比例。我们的方法不能直接估计分支依赖的需求。然而，它可以根据历史上的供过于求或供不应求将分支机构分类为给定数量的集群。这种对分支的分类可以迭代地用于适应未来供需的分支分布。
---
英文标题：
《Demand forecasting for companies with many branches, low sales numbers
  per product, and non-recurring orderings》
---
作者：
Sascha Kurz and Joerg Rambau
---
最新提交年份：
2008
---
分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
--
一级分类：Mathematics        数学
二级分类：Optimization and Control        优化与控制
分类描述：Operations research, linear programming, control theory, systems theory, optimal control, game theory
运筹学，线性规划，控制论，系统论，最优控制，博弈论
--

---
英文摘要：
  We propose the new Top-Dog-Index to quantify the historic deviation of the supply data of many small branches for a commodity group from sales data. On the one hand, the common parametric assumptions on the customer demand distribution in the literature could not at all be supported in our real-world data set. On the other hand, a reasonably-looking non-parametric approach to estimate the demand distribution for the different branches directly from the sales distribution could only provide us with statistically weak and unreliable estimates for the future demand. Based on real-world sales data from our industry partner we provide evidence that our Top-Dog-Index is statistically robust. Using the Top-Dog-Index, we propose a heuristics to improve the branch-dependent proportion between supply and demand. Our approach cannot estimate the branch-dependent demand directly. It can, however, classify the branches into a given number of clusters according to an historic oversupply or undersupply. This classification of branches can iteratively be used to adapt the branch distribution of supply and demand in the future.
---
PDF链接：
https://arxiv.org/pdf/0804.1414