Abstract
Interactive evolutionary computation (IEC) is a method to optimize media contents suited to user’s subjective feelings and preferences. Previous IECs employed various evolutionary algorithms, and most of them employed Genetic Algorithm (GA). The interactive type of GA is called IGA, and the IGA is applied to create user’s media content such as computer graphics, music, and sound. As a special application of the IGA, the creation of the scent was already proposed. In the IGA related to the scent, the intensity of the source aromas was treated as variable of GA individuals. In this study, the IGA is applied to create the flavor suited to beverage. The soda water with no sugar is treated as the beverage. It is popular among health-minded people, and some of the soda waters wear a flavor. In other words, the purpose of this study is to create a good flavor suited to soda water by reflecting each user’s feeling using IGA. In the use of the IGA, the user looks at the soda water with no sugar and smells the mixed flavor. In the mixture of the source aromas, Aromageur is used in the system. To investigate the fundamental efficiency of the IGA, a smelling experiment was conducted. The target of creation was “delicious” flavor for soda water, and six aroma oils were used as the source oils. The significant increase in fitness value was observed.
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References
McGann, J.P.: Poor human olfaction is a 19th-century myth. Science 356(6338), eaam7263 (2017)
Dawkins, R.: The Blind Watchmaker, Norton (1986)
Takagi, H.: Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation. Proc. IEEE 89(9), 1275–1296 (2001)
Holland, J.H.: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence. The University of Michigan Press, Ann Arbor (1975)
Goldberg, D.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Professional, Reading (1989)
Fukumoto, M., Imai, J.: Design of scents suited with user’s Kansei using interactive evolutionary computation. In: Proceedings of the International Conference on Kansei Engineering and Emotion Research 2010, pp. 1016–1022 (2010)
Fukumoto, M., Inoue, M., Imai, J.: User’s favorite scent design using paired comparison-based interactive differential evolution. In: Proceedings of the IEEE Congress on Evolutionary Computation 2010, pp. 4519–4524 (2010)
Fukumoto, M., Koga, S., Inoue, M., Imai, J.: Interactive differential evolution using time information required for user’s selection: in a case of optimizing fragrance composition. In: Proceedings of the IEEE Congress on Evolutionary Computation 2015, pp. 2192–2198 (2015)
Fukmoto, M., Wakiyama, R., Nomura, K.: Creation of fragrance suited to a product based on interactive tabu search. In: Proceedings of the FIT 2017, pp.159–162 (2017). (in Japanese)
Osgood, C.E., Suci, G.K., Tannenbaum, P.: The Measurement of Meaning. University of Illinois Press, Champaign (1957)
ASAHI web site. https://www.asahigroup-holdings.com/en/brand/wilkinson/
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Fukumoto, M., Yoshimitsu, S. (2021). Search for a Flavor Suited to Beverage by Interactive Genetic Algorithm. In: Saeed, K., Dvorský, J. (eds) Computer Information Systems and Industrial Management. CISIM 2021. Lecture Notes in Computer Science(), vol 12883. Springer, Cham. https://doi.org/10.1007/978-3-030-84340-3_14
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DOI: https://doi.org/10.1007/978-3-030-84340-3_14
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