Applying Artificial Bee Colony Algorithm to An Interactive Evolutionary Computation

Abstract

We apply an artificial bee colony (ABC) algorithm to interactive evolutionary computation (IEC) method for multimodal retrieving of candidate solutions. Previous works have proposed IEC systems using a parallel interactive tabu search algorithm (PITS) that generates multiple tabu search algorithm (TS) retrievals and hybrid a genetic algorithm (GA) that global retrieving method and a TS that local retrieving method for multimodal retrieving. However, the PITS cannot efficiently retrieve candidate solutions and has complicated algorithm. Also, the hybrid GA–TS hard to retrieve candidate solutions if the user has a more multimodal preference. Then, we propose an IEC method with ABC algorithm for multimodal and simultaneously retrieving of candidate solutions. In this study, we perform a numerical simulation with a pseudo user that imitates multimodal preferences as target individuals instead of a real user. The results show that the proposed method can retrieve multimodal candidate solutions in conditions with limited number of candidate solutions and bees.