Advances in population synthesis: fitting many attributes per agent and fitting to household and person margins simultaneously
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Agent-based microsimulation models of transportation, land use or other socioeconomic processes require an initial synthetic population derived from census data, conventionally created using the iterative proportional fitting (IPF) procedure. This paper introduces a novel computational method that allows the synthesis of many more attributes and finer attribute categories than previous approaches, both of which are long-standing limitations discussed in the literature. Additionally, a new approach is used to fit household and person zonal attribute distributions simultaneously. This technique was first adopted to address limitations specific to Canadian census data, but could also be useful in U.S. and other applications. The results of each new method are evaluated empirically in terms of goodness-of-fit.
KeywordsIterative proportional fitting Population synthesis Microsimulation Agent-based Census microdata Transportation models Trip forecasting
This research was supported by funding from an Ontario Graduate Scholarship, the Transportation Association of Canada, and a Transport Canada Transportation Planning and Modal Integration grant. The authors would also like to thank Laine Ruus of the University of Toronto Data Library for her invaluable assistance.
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