Interactive Genetic Algorithm with fitness modeling for the development of a color simulation system based on customer’s preference

Rodriguez, Ladys; Diago, Luis; Hagiwara, Ichiro

doi:10.1007/s13160-011-0032-2

Cited by 13 publications

(16 citation statements)

References 19 publications

(38 reference statements)

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“…Rodriguez and his team proposed using IGA to design the surface color of buildings. They constructed a userpreferred color scheme by combining the algorithm with a neural network to lower user fatigue 5 . Takekata, Li and colleagues used IGA to process images to satisfy users' emotional and psychological needs to meet users' demands [6][7] .…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

Application of Interactive Genetic Algorithm based on hesitancy degree in product configuration for customer requirement

Dou¹,

Zong²

2014

IJCIS

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With significant impact on the personalized product configuration, Interactive Genetic Algorithm is introduced to respond to customer requirement. For the user could conveniently design their favorite product and interact with the system by a graphical interface, the car console conceptual design system is established. And IGA based on hesitancy degree is proposed in this paper to reduce user's uncertainty or fuzzy feeling. By repeating the simulation experiment, the results validate the effectiveness of the proposed method in this paper.

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Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

Application of Interactive Genetic Algorithm based on hesitancy degree in product configuration for customer requirement

Dou¹,

Zong²

2014

IJCIS

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“…Other problems are: the lack of real fitness and the fatigue of user caused by the evaluation process. For these reasons, several techniques have been used to collect user subjective evaluations and built the evaluation function as a modeling fitness function [11], [12], [13], [14] where user's evaluation is replaced with lightweight approximations that adapts with the population. Fitness modeling methods are discussed in [13] .…”

Section: Introductionmentioning

confidence: 99%

“…Fitness modeling methods are discussed in [13] . Support vector machines (SVM) [12] and artificial neural networks (ANN) [13], [14] have been proposed to synthesize a fitness model based on user evaluation. However, as only a small number of samples must be obtained because it would be troublesome for customers to provide their preferences from many samples, prediction for very small datasets is still an unsolved problem.…”

Section: Introductionmentioning

confidence: 99%

“…In previous color recommendation systems (e.g. [8], [14]), the evaluation function did not consider that customer evaluations change with time and depends on the context presented during the evaluation process. Also, customers are overloaded by color combinations to consider and they may not have the time or knowledge to personally evaluate all color combinations in a product design.…”

Section: Introductionmentioning

confidence: 99%

“…As this paper is a continuation of our work [14], the general outline of previous system is explained in section II. Functionality improvements in comparison with [14] are highlighted. New contributions of this paper are described in section III and IV.…”

Section: Introductionmentioning

confidence: 99%

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Color recommendation system combining design concepts with interactive customers preference modeling from context changes

Rodriguez

Diago

Hagiwara

2010

IEEE Congress on Evolutionary Computation

Self Cite

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Colors play an important role for customers in making decisions on what they like or dislike. Frequently, customers are overloaded by color combinations to consider and they may not have the time or knowledge to personally evaluate all these combinations in a product design. This paper proposes a color recommendation system which includes design concepts as rules constraining the interactive search made by genetic algorithms to follow customer preferences. As the search space is very large and it changes with contextual information, proposed system combines graph coloring techniques with artificial neural networks to keep color restrictions during system evolution and model the fitness function provided by customers. In order to illustrate an application of proposed system, building images are used as example. After including conceptual coloring rules for building images in the system by two different methods, a questionnaire study was used to verify which approach suggested better images according to customer preferences. Experiments demonstrate that only if contextual information is included in the learning process system predictions keep close to customer's evaluation.

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Research on color optimization of tricolor product considering color harmony and users' emotion

Guo

Nagamachi

et al. 2019

Color Research & Application

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There are few studies on the tricolor design optimization, and the influence of color‐area ratio on users' emotion has been ignored. This article aims to achieve multiobjective optimization of tricolor product color design. Two modes of color‐area ratio are put forward. Using the proposed method of generating tricolor schemes, 368 tricolor schemes of the representative baby carriage are designed. Through questionnaire survey, color images are screened, and combined with correlation analysis and factor analysis, five perceptual features of color design are determined as “Order,” “Excitement,” “Temperature,” “Color harmony,” and “Users' emotional preference.” From two perspectives of color information processing, radial basis function neural networks are used to construct two emotional evaluation models. By integrating the radial basis function neural networks and a genetic algorithm, this study achieves multiobjective optimization of tricolor product color design for two optimization objectives of color harmony and users' emotional preference. Verification results show that the optimization schemes are significantly better than other schemes. Due to similar product characteristics, children's electric car is utilized to verify the generalization capability of the optimization method proposed in this article. It has been demonstrated that the optimization schemes achieve higher scores than randomly selected color schemes and the actual subjective scores match with the predicted scores computed by the color optimization method.

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Interactive Genetic Algorithm with fitness modeling for the development of a color simulation system based on customer’s preference

Cited by 13 publications

References 19 publications

Application of Interactive Genetic Algorithm based on hesitancy degree in product configuration for customer requirement

Application of Interactive Genetic Algorithm based on hesitancy degree in product configuration for customer requirement

Color recommendation system combining design concepts with interactive customers preference modeling from context changes

Research on color optimization of tricolor product considering color harmony and users' emotion

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