Title: A novel framework for facility location evaluation

Authors: Ming Xie, Wenjun Yin, Bin Zhang, Jinyan Shao, Li Xia, Jin Dong

Addresses: IBM China Research Laboratory, Diamond Building A, Zhongguancun Software Park, Haidian District 100193, Beijing, China. ' IBM China Research Laboratory, Diamond Building A, Zhongguancun Software Park, Haidian District 100193, Beijing, China. ' IBM China Research Laboratory, Diamond Building A, Zhongguancun Software Park, Haidian District 100193, Beijing, China. ' IBM China Research Laboratory, Diamond Building A, Zhongguancun Software Park, Haidian District 100193, Beijing, China. ' IBM China Research Laboratory, Diamond Building A, Zhongguancun Software Park, Haidian District 100193, Beijing, China. ' IBM China Research Laboratory, Diamond Building A, Zhongguancun Software Park, Haidian District 100193, Beijing, China

Abstract: Is a given location appropriate to set a facility, and if it is, how will this facility perform? This is denoted as the facility location problem, which has attracted interests of academic researchers and industrial practitioners. This problem is traditionally considered in spatial analysis and forecasting literature. However, existing methods can hardly handle the problem well because of the fragmented information and insufficient training data. In this paper, we present a novel framework which combines spatial analysis and forecasting analysis for facility location. Firstly, a classifier is built on spatial information to evaluate locations| environmental patterns. For each pattern, a predictor is then constructed to predict facility performance. Besides, we also propose a data aggregation method to pre-process raw spatial data, and a semi-supervised learning method to expand insufficient training data. Experimental results of a case study demonstrate the effectiveness of the framework on supporting real-world facility location decisions.

Keywords: facility locations; geographic information systems; GIS; data mining; spatial analysis; forecasting analysis; location evaluation; environmental patterns; performance prediction; predictors; decision making; services operations; services management; informatics.

DOI: 10.1504/IJSOI.2010.031050

International Journal of Services Operations and Informatics, 2010 Vol.5 No.1, pp.75 - 94

Available online: 19 Jan 2010 *

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