DocumentCode
2225053
Title
Investigation of efficiency of manipulation in interactive Tabu Search for optimizing fragrance composition
Author
Fukumoto, Makoto ; Koga, Shimpei
Author_Institution
Department of Computer Science and Engineering, Fukuoka Institute of Technology, Fukuoka, Japan
fYear
2015
fDate
25-28 May 2015
Firstpage
2589
Lastpage
2594
Abstract
Fragrance is one of important media types used in our daily life, and it is ideal that using media content suited to each user. However, adjustment of fragrance composition is difficult for most of general users. Interactive Evolutionary Computation (IEC) is known as an efficient method to optimize media contents, and we have already proposed some IECs for optimizing fragrance composition. To enhance the optimization ability of IEC, some previous studies proposed that IEC accepts user´s manipulations on solution candidate in IEC. Our previous study proposed Interactive Tabu Search (ITS) for optimizing fragrance composition with the user´s manipulation, and a fundamental efficiency of the ITS was investigated. However, the efficiency was not investigated with comparing experiment. Purpose of this study was to investigate the efficiency of the manipulation in the ITS by comparing with ITS without any manipulation. With these two experimental conditions, smelling experiments were conducted. In result of optimizing experiment, relatively one direction changes in intensity of some aroma sources were observed in both conditions. In result of evaluating experiment, maximum mean fitness was observed in the final best solution in the ITS with manipulation. The fitness of the best solutions in both conditions was significantly higher than solution candidate in the initial generation. However, significant difference between the two conditions was not observed.
Keywords
Evolutionary computation; Genetic algorithms; IEC; IEC Standards; Media; Optimization; Search problems; Fragrance Composition; Interactive Evolutionary Computation; Manipulation; Relaxation; Tabu Search;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location
Sendai, Japan
Type
conf
DOI
10.1109/CEC.2015.7257207
Filename
7257207
Link To Document