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Abstract

Land use microsimulation requires the preparation of a set of microdata for the base year. Most existing procedures used for the synthesis of population data are based on the iterative proportional fitting method, in which the number of individuals in each cell of the cross-classification table is estimated. Such a procedure is referred to as the cell-based approach in this study. The approach is based on predefined categories of individuals. Originally, however, these individuals have continuous attributes. Therefore, a different type of categorization would yield a different classification table, which would change the end results of the analysis. In this paper, this phenomenon is referred to as the modifiable attribute cell problem (MACP). It is similar to the modifiable area unit problem that arises when spatial data are aggregated into zones. This paper addresses MACP and proposes a method to determine the best combination of the categories. The solution of MACP is considered to be the minimization of the number of cells in a table with respect to the key output variable that has been defined and used as an evaluation criterion. Because of the computational difficulty resulting from the combination explosion, symbiotic evolution, which is a kind of genetic algorithm, is used. Finally, a case study is presented for the Sapporo metropolitan area of Japan.

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Modifiable Attribute Cell Problem and Solution Method for Population Synthesis in Land Use Microsimulation

Abstract

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