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Application of combined Kano model and interactive genetic algorithm for product customization

JOURNAL OF INTELLIGENT MANUFACTURING 2019年第7期30卷 2587-2602页

作者： Dou, Runliang Zhang, Yubo Nan, Guofang Tianjin Univ Coll Management & Econ Tianjin 300072 Peoples R China

interactive genetic algorithms (IGAs) have been applied in industrial design to quickly respond to customers' personalized demand and to achieve customization. However, unreasonable recognition and improper configuration of customization attributes may increase the design complexity, impair efficiency and lead to user fatigue. In this paper, a combined Kano model and IGA approach is proposed for more effective product customization to conduct customer-driven product design by fully considering their individual preferences and simultaneously enhancing effective user involvement. The approach uses the Kano model to recognize different customization attributes and rank them in order of their influence on customer satisfaction. The model then dynamically adjusts these attributes for customization in the IGA-based product design process to more quickly find a satisfying design scheme without leading to user fatigue. A computer-aided design system prototype is developed in the context of the customized design of tablet PCs to prove the maneuverability and effectiveness of the proposed approach. The experimental results demonstrate that the approach could improve customization efficiency to a large extent and fully relieve user fatigue by expediting the process of finding satisfying design individuals for customers.

关键词： Product customization interactive genetic algorithm Kano model User fatigue

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Pattern design and optimization of yarn-dyed plaid fabric using modified interactive genetic algorithm

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JOURNAL OF THE TEXTILE INSTITUTE 2020年第11期111卷 1652-1661页

作者： Zhang, Ning Pan, Ruru Wang, Lei Wu, Yang Gao, Weidong Jiangnan Univ Key Lab Ecotext Minist Educ Wuxi Jiangsu Peoples R China

With the advancing consumption level, it is difficult to shorten the product cycle and meet consumer's demands during the design process of yarn-dyed plaid fabric. In order to extract consumers' preferences and obtain timely feedbacks, a novel method using modified interactive genetic algorithm (IGA) is proposed for pattern design and optimization of yarn-dyed plaid fabric in this paper. Initially, the pattern of plaid fabric was encoded using the natural number code. The population was initialized based on common colour schemes. Then, survival of the fittest was performed as the selection operator to extinguish unsatisfactory patterns and preserve satisfactory patterns. Subsequently, common crossover operator and mutation operator, special mutation operator including addition and deletion were implemented to generate offspring. Moreover, users can manipulate individuals directly for convergence acceleration during the evolutionary process. Finally, the experiment was carried out by twenty-four users of different age groups and genders. Experimental results indicate that the application of IGA is feasible and efficient, which can supply design references to the designer.

关键词： Yarn-dyed plaid fabric pattern design and optimization interactive genetic algorithm subjective evaluation

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3D modeling design and rapid style recommendation of polo shirt based on interactive genetic algorithm

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JOURNAL OF ENGINEERED FIBERS AND FABRICS 2020年第15期15卷

作者： Zhang Zhuo Cong Honglian Jiangnan Univ Engn Res Ctr Knitting Technol Minist Educ 1800 Lihu Rd Wuxi 214122 Jiangsu Peoples R China

This paper proposes a design method for personalized 3D modeling and a rapid style recommendation of polo shirts based on interactive genetic algorithms. Through the research on the parametric multi-style design method of polo shirts, this paper proposes 3D design methods such as the conversion of 3D models, component splicing, and stripes matching mapping rules. In addition, we establish a coded component library of style parts and striped designs to realize the component modeling of tailor-made styles for polo shirts. Besides, the interactive genetic algorithm (IGA) is introduced in the article. Through the algorithm coding, initial population generation, selection, using the scoring mechanism to obtain the user's suitability evaluation of the program, crossover, and mutation, etc., gradually generating a user-satisfied polo shirt style model design plan, a personalized rapid style recommendation of the user-oriented polo shirt is established. This system can present tailored polo shirt style for customers, and WYSIWYG, to find the most favorite clothing styles for customers and lower the threshold of clothing design expertise.

关键词： Clothing modeling interactive genetic algorithm virtual display

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Pattern retrieval of yarn-dyed plaid fabric based on modified interactive genetic algorithm

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COLOR RESEARCH AND APPLICATION 2020年第6期45卷 1143-1152页

作者： Zhang, Ning Pan, Ruru Wang, Lei Meng, Shuo Gao, Weidong Jiangnan Univ Minist Educ Key Lab Ecotext Wuxi Peoples R China

With the development of perceptual consumption, consumers sometimes cannot explicitly describe the purchase demands or only based on impression, like the color perception and aesthetic experience. Based on the consumer's expression, it is difficult to design a new fabric by repeated proofing to meet the consumer's demands. To retrieve the existing patterns incorporating human intuition and emotion, this study proposed a novel pattern retrieval method of yarn-dyed plaid fabric using modified interactive genetic algorithm. Each pattern was encoded based on the design elements and visual features were extracted to bridge the semantic gap between the designer and the consumer. Survival of the fittest and two special mutation operators, addition and deletion, were designed to increase the diversity of the generations. During the evolution, the generated patterns were replaced by the most similar patterns in the database based on visual features. Experimental results showed that the proposed scheme is feasible and effective to extract the consumer's preferences and retrieve satisfactory patterns, helping the factory obtain the process sheet to guide production and save labor and material resources.

关键词： color appearance interactive genetic algorithm pattern retrieval perception consumption yarn-dyed plaid fabric

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interactive genetic algorithm Oriented toward the Novel Design of Traditional Patterns

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INFORMATION 2019年第2期10卷

作者： Lv, Jian Zhu, Miaomiao Pan, Weijie Liu, Xiang Guizhou Univ Key Lab Adv Mfg Technol Minist Educ Guiyang 550025 Guizhou Peoples R China

To create alternative complex patterns, a novel design method is introduced in this study based on the error back propagation (BP) neural network user cognitive surrogate model of an interactive genetic algorithm with individual fuzzy interval fitness (IGA-BPFIF). First, the quantitative rules of aesthetic evaluation and the user's hesitation are used to construct the Gaussian blur tool to form the individual's fuzzy interval fitness. Then, the user's cognitive surrogate model based on the BP neural network is constructed, and a new fitness estimation strategy is presented. By measuring the mean squared error, the surrogate model is well managed during the evolution of the population. According to the users' demands and preferences, the features are extracted for the interactive evolutionary computation. The experiments show that IGA-BPFIF can effectively design innovative patterns matching users' preferences and can contribute to the heritage of traditional national patterns.

关键词： patterns with traditional national characteristics BP neural network surrogate model interactive genetic algorithm aesthetic evaluation

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interactive genetic algorithm for user-centered design of distributed conservation practices in a watershed: An examination of user preferences in objective space and user behavior

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WATER RESOURCES RESEARCH 2017年第5期53卷 4303-4326页

作者： Piemonti, Adriana Debora Babbar-Sebens, Meghna Mukhopadhyay, Snehasis Kleinberg, Austin Oregon State Univ Sch Civil & Construct Engn Corvallis OR 97331 USA Indiana Univ Purdue Univ Dept Comp & Informat Sci Indianapolis IN 46202 USA

interactive genetic algorithms (IGA) are advanced human-in-the-loop optimization methods that enable humans to give feedback, based on their subjective and unquantified preferences and knowledge, during the algorithm's search process. While these methods are gaining popularity in multiple fields, there is a critical lack of data and analyses on (a) the nature of interactions of different humans with interfaces of decision support systems (DSS) that employ IGA in water resources planning problems and on (b) the effect of human feedback on the algorithm's ability to search for design alternatives desirable to end-users. In this paper, we present results and analyses of observational experiments in which different human participants (surrogates and stakeholders) interacted with an IGA-based, watershed DSS called WRESTORE to identify plans of conservation practices in a watershed. The main goal of this paper is to evaluate how the IGA adapts its search process in the objective space to a user's feedback, and identify whether any similarities exist in the objective space of plans found by different participants. Some participants focused on the entire watershed, while others focused only on specific local subbasins. Additionally, two different hydrology models were used to identify any potential differences in interactive search outcomes that could arise from differences in the numerical values of benefits displayed to participants. Results indicate that stakeholders, in comparison to their surrogates, were more likely to use multiple features of the DSS interface to collect information before giving feedback, and dissimilarities existed among participants in the objective space of design alternatives.

关键词： interactive genetic algorithm optimization watershed human-computer interaction conservation planning

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Creation of Ideal User's Voice Using User's own UTAU Voice and interactive genetic algorithm 10

Creation of Ideal User's Voice Using User's own UTAU Voice a...

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Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) / 19th International Symposium on Advanced Intelligent Systems (ISIS)

作者： Inoue, Asami Nomura, Kota Fukumoto, Makoto Fukuoka Inst Technol Grad Sch Engn Comp Sci & Engn Fukuoka Fukuoka Japan Fukuoka Inst Technol Fac Informat Engn Fukuoka Fukuoka Japan

ISBN: (纸本)9781538626337

Since many books and papers on voice quality improvement are circulating around the world, we think that there are at least those who want to change their own voice. However, there is an image that voice quality improvement is difficult. The reason is that it is difficult to objectively evaluate user's oneself with voice training by user's oneself, and user cannot improve voice quality user's oneself easily. Therefore, in this research, we propose and verify the method of creating user's ideal voice, which is the goal when improving voice quality based on user's voice by using software UTAU and interactive genetic algorithm (IGA). As results of experiment, in a search experiment using IGA, the average and the maximum evaluation values increased significantly. Furthermore, using the best individuals found in this search by comparing significant increase was also observed (p<0.05). Therefore, it turns out that the proposed method has the possibility of making the ideal voice of the user.

关键词： UTAU interactive genetic algorithm Ideal Voice

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Improving the interactive genetic algorithm for customer-centric product design by automatically scoring the unfavorable designs

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HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES 2017年第1期7卷 1-18页

作者： Darani, Zahra Sheikhi Kaedi, Marjan Univ Isfahan Fac Comp Engn Hezar Jerib St Esfahan *** Iran

One of the effective factors in increasing sales is the consistency of products with the preference of the customers. Designing the products consistent with customer needs requires the engagement of customers in the product design process. One way to achieve this goal is the use of interactive evolutionary algorithms. During the running of such algorithms, the customer acts as a fitness function and imparts his/her opinion directly to the design process. Since these algorithms are usually iterated frequently, the user fatigue problem during interaction with them is a major challenge. The present study develops a method to tackle the user fatigue problem in the interactive genetic algorithm using the candidate elimination algorithm. In this method, customer preferences are gradually learned by applying the candidate elimination algorithm on the designs evaluated by the user in the early stages of algorithm. Using the learned preferences, designs which may not meet the customer preferences are discovered and automatically receive a predefined low score from the algorithm. The proposed method has been evaluated on the customer-centric design of book covers and its results have been compared with those of the two simple interactive genetic algorithm and multi-stage interactive genetic algorithm. The results are indicative of a considerable reduction of the number of algorithm generations, the number of chromosomes being evaluated by user, and the evaluating time in comparison with the two aforementioned methods. Reduction of these criteria leads to decrease of user fatigue. In addition, the proposed method has increased the user satisfaction.

关键词： interactive design Customer-centric product design interactive genetic algorithm User fatigue Candidate elimination algorithm

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Research on urban landscape design using the interactive genetic algorithm and 3D images

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Visualization in Engineering 2017年第1期5卷 1-10页

作者： Koma, Seiki Yamabe, Yuichiro Tani, Akinori Department of Architecture Graduate School of Engineering Kobe University 1-1 Rokkodai Nada Kobe 657-8501 Hyogo Japan

Background: Generally, there are different optimal solutions with regard to urban landscape planning depending on the area and the opinions and characteristics of community residents. Furthermore, when considering urban landscape and/or city-planning regulations, it is important to include residents’ opinions based on voluntary activities like participation in town development on a regional scale and its management. However, residents’ opinions are difficult to quantify, as many do not have specialized knowledge. Therefore, when an administrative body plans a city, a system to include residents’ opinions on urban landscape options is required. Methods: In this study, an optimization system for urban landscape design was proposed using an interactive genetic algorithm (IGA). In this system, three properties of an urban landscape, that is, wall surface positions, heights, and building textures, were varied and the resulting urban landscape images, developed using OpenGL, were subjectively evaluated by users. Weighted scores were then calculated using the paired comparison method. In this system, a site of 200 m × 70 m was assumed and 20 buildings were located on 20 m × 20 m lots. The building widths were fixed at 20 m, and wall positions from the sidewalk varied from 10 m to 20 m at 2 m intervals. The building heights varied from 20 m to 40 m at 4 m intervals, and eight building textures were considered. Two simulations were performed: Case 1, in which the three parameters were evaluated simultaneously;and Case 2, in which the three parameters were evaluated individually. The same 10 users participated in both cases. Following completion of each case, questionnaires were administered to users in which they were asked to confirm that the results obtained matched their expectations. Results: The results demonstrated that individual users were satisfied with the results generated based on their evaluations. In both cases, the results were obtained from the optimal result

关键词： interactive genetic algorithm Paired comparison method Urban landscape

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Asynchronous Distributed interactive genetic algorithm for Creating Music Melody Reflecting Multiple Users' Feelings 18

Asynchronous Distributed Interactive Genetic Algorithm for C...

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18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)

作者： Nomura, Kota Fukumoto, Makoto Fukuoka Inst Technol Grad Sch Engn Fukuoka Japan Fukuoka Inst Technol Dept Comp Sci & Engn Fukuoka Japan

ISBN: (纸本)9781509055043

In the area of product design, it is important that adding user's feelings on the products for emphasizing its value. interactive Evolutionary Computation (IEC) is known as a method that searches optimal or better media contents suited for each user's feelings. In terms of expanding the ability of IEC, some recent studies applied IEC into problem of multiple users. This study aims to create music melody suited for multiple users' feelings by employing parallel Distributed interactive genetic algorithm (DIGA). In this method, each of the users proceeds general interactive genetic algorithm (IGA) process by evaluating solution candidates subjectively. In some generations, solution candidates are exchanged between the users. With the exchange, each of the users is affected by other users' feelings. As a result of these processes, obtaining good solution suited for all users. We conducted listening experiments for investigating efficiency of the DIGA for creation of music melody. Ten persons participated in the experiment as subjects, and pair of the subjects participated in the IGA task simultaneously. Experimental results show that higher fitness was obtained in the final generation, and similar melody was obtained through exchange of solutions. To clarify the efficiency of the exchange of the asynchronous method, further study with comparing experiment including conditions synchronous is needed.

关键词： interactive genetic algorithm Distributed interactive genetic algorithm Music melody Multiple users

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