Comparing Transition Procedures in Modified Simulated-Annealing-Based Synthetic Reconstruction Method without Samples

Abstract

In this paper, we modify a synthetic reconstruction (SR) method without samples. The synthetic reconstruction method is a method to generate attributes of population such as age, sex and kinship within a family according to available statistics. Although the original SR method employs some individual samples that are collected to make a statistics, it is criticized that generated attributes are only within the samples used in the reconstruction process. In this paper, we employ a simulated annealing-based SR method without samples. We compare two types of generation methods of a candidate solution in a search of simulated annealing: changing age of an agent (age-change) or swapping ages of two agents (age-swap). Results of synthetic reconstruction show that age-change is better when we limit the number of search. On the other hand, age-swap is better when we have enough number of search for reconstructing a population.