Interactive Evolutionary Computation with Artificial Bee Colony Method for Multimodal Preferences Retrieval

Abstract

In this study, we apply an artificial bee colony (ABC) algorithm to the interactive evolutionary computation (IEC) method for the multimodal retrieval of candidate solutions in a Kansei space having multimodal preferences. Previous IEC methods often used a genetic algorithm (GA) method for evolutionary algorithm; retrieving multimodal candidates using these methods were difficult. Therefore, we propose an IEC method with the ABC algorithm for the multimodal and simultaneous retrieval of candidate solutions. We perform numerical simulations with a pseudo user that imitates multimodal preferences as target candidate solutions, instead of a real user. The practical aspect of the proposed method assumes to employ user gaze information for evaluating candidates. Moreover, we set the numerical simulation condition based on a real situation. The results show that the proposed method was more effective for retrieving multimodal candidates than the compared method for practical numbers of candidates and generations.