Interactive Tabu Search with Paired Comparison for Optimizing Fragrance
Makoto Fukumoto, M. Inoue, Keiji Kawai, Jun‐ichi Imai · 2013
Interactive evolutionary computation (IEC) is known as an effective method to optimize media contents to user's subjective feelings. Previous IEC studies employed various evolutionary algorithms, and one of them applied Tabu Search (TS) algorithm. This method was named Interactive Tabu Search (ITS). In the ITS, users have to select the best individual from population. The authors applied ITS for creating fragrance in our previous study, and blended fragrances composed of several aroma sources are corresponded to individuals in ITS. Strength of each aroma source was target of optimization. However, it seemed difficult for the users to decide the best fragrance from several fragrances with sequential presentation. This study focuses on proposing a new ITS method using paired comparison. The successive paired comparisons are used for deciding the best individual from population like tournament selection. Furthermore, this study investigated the efficiency of the proposed ITS method through smelling experiments.