Goodness-of-Fit Evaluation Method for Agent-Based Household Microdata Sets Composed of Generalized Attributes

Abstract

Microsimulation models of land use characterize attributes of a household and its location, referred to as microdata in this study. However, methods for evaluating the goodness of fit between estimated and observed sets of agent-based microdata have not been investigated extensively. Although the attributes of a household include various items, such as the relationship with the household head and ages of the members, housing type and spatial location, number of cars owned, and income, the attributes can be classified into general categories. The objective of the present study is to develop a goodness-of-fit evaluation method for agent-based household microdata sets composed of generalized attributes. First, a distance measure between the estimated and observed microdata for each household is defined. In this definition a generalized scheme is introduced, whereby attributes are structured by the household composition, attributes of the member, and attributes of the household as a whole. The goodness of fit is measured on the basis of the minimum sum of distances for all households in the study area. The calculation cannot be carried out with just a conventional algorithm for microdata of a typical size because the number of calculations increases in proportion to the factorial (N!) of the number (N) of agents. Therefore, a genetic algorithm, especially one using symbiotic evolution, is developed to solve the problem. The effectiveness of the method in regard to accuracy and calculation feasibility is confirmed by using person trip survey data for the Sapporo metropolitan area in Japan.

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