Multi-objective optimization of visual and tactile desirability of wooden textures

被引:0
|
作者
Tamura, Ayaka [1 ]
Okamoto, Shogo [1 ]
机构
[1] Tokyo Metropolitan Univ, 6-6 Asahigaoka, Hino, Tokyo 1910065, Japan
关键词
Texture; Optimization; Appearance; Tactile pleasantness; Taguchi method; PERCEPTION; VISION; DESIGN; TOUCH;
D O I
10.1299/jamdsm.2024jamdsm0077
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Affective and aesthetic qualities of textures largely depend on their visual and tactile features. However, to date, no systematic methods have been established for the design of such textures. This study confirms the feasibility of the Taguchi method for the multi-objective optimization of texture appearance and tactile pleasantness. To this end, texture stimuli are created using a medium-density fiberboard and laser cutting with several design parameters, including the dimensions and number of engraved figures. Each texture is evaluated based on its appearance and tactile pleasantness. In the multi-objective optimization process using the Taguchi method, a single-objective optimization is performed on iteratively updated sample sets. After several iterations of single-objective process, three non-dominated solutions, namely the Pareto set, are identified with respect to visual and tactile pleasantness. This study demonstrates the effectiveness of the multi-objective Taguchi method to optimize multimodal textured stimulations.
引用
收藏
页数:12
相关论文
共 50 条
  • [21] Splitting for Multi-objective Optimization
    Qibin Duan
    Dirk P. Kroese
    Methodology and Computing in Applied Probability, 2018, 20 : 517 - 533
  • [22] Multi-objective Whale Optimization
    Kumawat, Ishwar Ram
    Nanda, Satyasai Jagannath
    Maddila, Ravi Kumar
    TENCON 2017 - 2017 IEEE REGION 10 CONFERENCE, 2017, : 2747 - 2752
  • [23] Evolutionary Multi-Objective Optimization
    Deb, Kalyanmoy
    GECCO-2010 COMPANION PUBLICATION: PROCEEDINGS OF THE 12TH ANNUAL GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2010, : 2577 - 2602
  • [24] Multi-objective optimization (MO)
    Balling, RJ
    OPTIMAIZATION IN INDUSTRY, 2002, : 337 - 338
  • [25] Splitting for Multi-objective Optimization
    Duan, Qibin
    Kroese, Dirk P.
    METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, 2018, 20 (02) : 517 - 533
  • [26] Progressive Multi-Objective Optimization
    Sorensen, Kenneth
    Springael, Johan
    INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2014, 13 (05) : 917 - 936
  • [27] Multi-objective optimization of mechanisms
    Palcak, Frantisek
    Preszinsky, Gellert
    X. INTERNATIONAL CONFERENCE ON THE THEORY OF MACHINES AND MECHANISMS, PROCEEDINGS, 2008, : 447 - 452
  • [28] The Multi-Objective Polynomial Optimization
    Nie, Jiawang
    Yang, Zi
    MATHEMATICS OF OPERATIONS RESEARCH, 2024, 49 (04) : 2723 - 2748
  • [29] Evolutionary multi-objective optimization
    Coello Coello, Carlos A.
    Hernandez Aguirre, Arturo
    Zitzler, Eckart
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 181 (03) : 1617 - 1619
  • [30] Desirability-Based Multi-Objective QSAR in Drug Discovery
    Cruz-Monteagudo, Maykel
    Cordeiro, M. Natalia D. S.
    Tejera, Eduardo
    Rosa Dominguez, Elena
    Borges, Fernanda
    MINI-REVIEWS IN MEDICINAL CHEMISTRY, 2012, 12 (10) : 920 - 935