Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
Differential evolution is a population-based stochastic search technique for solving optimization problems in a continuous space. DE belongs to the class of evolutionary algorithms and is similar to Genetic Algorithms (GA). Due to its simplicity, effectiveness and robustness, DE has been applied to a variety of real-world problems. Interactive Differential Evolution (IDE) is a kind of Interactive Evolutionary Computation (IEC) that user evaluate the individuals for generation alternation. In this paper, we propose a fashion coordination system that supports users to choose their favorite color coordination. In IEC, it is important to reduce the fatigue of a user during the evaluation process. Therefore, we introduce evolutionary level to DE algorithm and propose an fast method for reducing the number of evaluations. Finally, the proposed system confirmed the validity through experiments.
