Abstract
In this paper, we propose an interactive genetic algorithm that obtains valuations of individuals from multiple people. This technique is effective for consensus building and in bringing together many opinions for cases such as allowing multiple people to design clothes together. With an interactive genetic algorithm in which multiple people participate, a simple and easy evaluation interface is required. This technique determines the solution group of the genetic algorithm by the tournament method. In this technique, two solution candidates are presented to the evaluator. The evaluator then votes between the two solution candidates. A large number of evaluators judge the solution candidate's superiority or inferiority, and the relative superiority or inferiority of the two solutions is decided. The evaluation value of all solution candidates is decided depending on a relative value of the superiority or inferiority of the two solutions based on the results of this tournament competition. The obtained solution reflects the opinion of all evaluators well. In this paper, the effectiveness of the proposed technique was verified by a simulation using multiple evaluation agents in place of real evaluators. In each tournament competition, the result when 60% of all evaluation agents participated in a vote almost equaled the result when all the evaluation agents participated. This means the load to which the evaluator evaluates the solution candidate can be reduced by 40%. Moreover, we compared the proposed technique with a general voting method that uses a large number of evaluators voting for the first good individual from among all solution candidates in a displayed list. We confirmed that the proposed technique was more effective than a general voting method from the viewpoint that many participants are satisfied.
