Aggregating Data for the Flow-Intercepting Location Model: A Geographic Information System, Optimization, and Heuristic Framework Weiping Zeng, 1 Ignacio Castillo, 2 Michael John Hodgson 3 1 21st Century Mapping Solutions Inc., Calgary, AB, Canada T3G 1R1, 2 School of Business and Economics, Wilfrid Laurier University, Waterloo, ON, Canada N2L 3C5, 3 Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E3 Flow-intercepting problems have received considerable interest, represented by about 40 academic publications, since the early 1990s. Point-based demand aggregation also has received much research interest in both industry and academia. Systematic studies of flow data aggregation for flow-intercepting problems have not, however, been reported to date. Our research highlights the importance of flow-based demand aggregation and develops a framework for aggregating such demand. This framework represents the first systematic study of aggregation for flow-intercepting location mod- els (FILM). The standard FILM is the perfect model for our goals—its aggregation errors are easy to understand and its outputs are easy to measure and compare. Our research uses geographic information systems, optimization, and heuristic technologies to ex- amine the special network flow structure of a real-world transportation system and to develop a comprehensive method of aggregating data for the standard FILM. We apply our method to the 2001 afternoon peak traffic data for Edmonton, Alberta (the sixth largest Canadian city) and find this application to be extremely efficient. We discover that in the Edmonton traffic flow network, a large number of paths have very small flows; major flows are concentrated in a limited number of paths; and a large number of small-flow paths and a large number of low-flow nodes on local streets have neg- ligible effects on facility locations for FILM. We speculate that most real-world trans- portation systems may have similar characteristics. Introduction One of the most important ways an industrial firm, retail outlet, or government agency can enhance its chances of success is to identify good locations for its Correspondence: Weiping Zeng, 21st Century Mapping Solutions Inc., 1220 Ranchlands Way, NW, Calgary, AB, Canada T3G IR1 e-mails: zeng@ualberta.ca, zeng@21maps.com Submitted: March 6, 2008. Revised version accepted: March 30, 2009. Geographical Analysis 42 (2010) 301–322 r 2010 The Ohio State University 301 Geographical Analysis ISSN 0016-7363