Parallel Computing for Reconstructing Large-Scale Household Composition from Statistics for Agent-Based Social Simulations

In this paper, we employ parallel computing techniques to reconstruct large-scale household compositions for micro-simulations (MS) or agent-based simulations (ABS). For enabling MS or ABS, each household composition such as ages, occupations, or other properties of each member of a household should be prepared before simulations. However real household compositions are not available to researchers due to privacy or security reasons. In this paper, we propose a method to reconstruct a large-scale household composition based on statistics using parallel computing techniques. In order to generate artificial populations as soon as possible, parallel computing techniques are essential in reconstruction methods. In this paper, we show a challenge in an application of parallel computing to a previously proposed reconstruction method, and how to cope with that challenge.