2013 Volume 6 Issue 2 Pages 124-130
Although a lot of researchers have interests to social simulations recently, many of their outcomes can show just abstract lessons over simple settings in their social simulations. It is understandable because complicate settings will make their social simulation tool difficult to understand and tune its parameters. There is a dilemma between simple settings with abstract lessons and difficult settings with difficult tool tuning. In this paper, it is shown that how social simulation tools can be used to make a policy proposal for polling place assignment. In the previous study of authors, a model was proposed for a decision making for each voter in an election. The change of the polling places was considered in a city, Takatsuki, Osaka Prefecture, Japan, to increase the voter turnout and to reduce the number of polling places. A method was also proposed to identify regional polling parameters in an election using real voter turnout records. With those regional polling parameters, selection and assignment of polling places to each region was done using an Evolutionary Multiobjective Optimization (EMO) algorith. Several sets of solutions were found that increase the voter turnouts and reduce the number of the polling places. In this paper, the authors show several practical results after consulting the office of the board of elections in the target city. In order to utilize outcomes of social simulations practically, they are advised that they should show the difference between the current voting assignment and the proposed one in order to announce those who should vote in a different station. They are also advised to show how to support those who should go to farther polling stations after the change of polling stations. To meet these requests from the office, they simulate a case with free shuttle bus service using our model.