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Computational Intelligence and Neuroscience
Volume 2017, Article ID 9740278, 8 pages
https://doi.org/10.1155/2017/9740278
Research Article

A Method for Consensus Reaching in Product Kansei Evaluation Using Advanced Particle Swarm Optimization

School of Construction Machinery, Chang’an University, Xi’an 710064, China

Correspondence should be addressed to Yan-pu Yang; nc.ude.dhc@upnaygnay

Received 17 November 2016; Accepted 16 January 2017; Published 12 February 2017

Academic Editor: Elio Masciari

Copyright © 2017 Yan-pu Yang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Y. Yang, D. Chen, R. Gu, Y. Gu, and S. Yu, “Consumers' Kansei needs clustering method for product emotional design based on numerical design structure matrix and genetic algorithms,” Computational Intelligence and Neuroscience, vol. 2016, Article ID 5083213, 11 pages, 2016. View at Publisher · View at Google Scholar
  2. Y.-M. Chang and C.-W. Chen, “Kansei assessment of the constituent elements and the overall interrelations in car steering wheel design,” International Journal of Industrial Ergonomics, vol. 56, pp. 97–105, 2016. View at Publisher · View at Google Scholar
  3. M. Nagamachi, “Kansei Engineering: a new ergonomic consumer-oriented technology for product development,” International Journal of Industrial Ergonomics, vol. 15, no. 1, pp. 3–11, 1995. View at Publisher · View at Google Scholar · View at Scopus
  4. M. Nagamachi, “Kansei engineering as a powerful consumer-oriented technology for product development,” Applied Ergonomics, vol. 33, no. 3, pp. 289–294, 2002. View at Publisher · View at Google Scholar · View at Scopus
  5. M. Nagamachi, “Kansei engineering and kansei evaluation,” in International Encyclopedia of Ergonomics and Human Factors, W. Karwowski, Ed., vol. 3, CRC Press, Boca Raton, Fla, USA, 2006.
  6. P. Lévy, “Beyond kansei engineering: the emancipation of kansei design,” International Journal of Design, vol. 7, no. 2, pp. 83–94, 2013. View at Google Scholar
  7. K. Grimsæth, Kansei Engineering Linking Emotions and Product Features, 2005.
  8. A. T. Pambudi, M. R. Suryoputro, A. D. Sari, and R. D. Kurnia, “Design of Lesehan chair by using Kansei engineering method and anthropometry approach,” in Proceedings of the International Conference on Engineering and Technology for Sustainable Development (ICET4SD '15), Yogyakarta, Indonesia, 2015.
  9. A. Shergian and T. Immawan, “Design of innovative alarm clock made from bamboo with kansei engineering approach,” Agriculture and Agricultural Science Procedia, vol. 3, pp. 184–188, 2015. View at Google Scholar
  10. B. Razza and L. C. Paschoarelli, “Affective perception of disposable razors: a kansei engineering approach,” Procedia Manufacturing, vol. 3, pp. 6228–6236, 2015. View at Publisher · View at Google Scholar
  11. N. K. Chuan, A. Sivaji, M. M. Shahimin, and N. Saad, “Kansei engineering for e-commerce sunglasses selection in Malaysia,” Procedia—Social and Behavioral Sciences, vol. 97, pp. 707–714, 2013. View at Publisher · View at Google Scholar
  12. T. K. Djatna and W. D. Kurniati, “A system analysis and design for packaging design of powder shaped fresheners based on Kansei engineering,” Procedia Manufacturing, vol. 4, pp. 115–123, 2015. View at Publisher · View at Google Scholar
  13. M.-C. Chen, C.-L. Hsu, K.-C. Chang, and M.-C. Chou, “Applying Kansei engineering to design logistics services—a case of home delivery service,” International Journal of Industrial Ergonomics, vol. 48, pp. 46–59, 2015. View at Publisher · View at Google Scholar · View at Scopus
  14. M.-S. Huang, H.-C. Tsai, and T.-H. Huang, “Applying Kansei engineering to industrial machinery trade show booth design,” International Journal of Industrial Ergonomics, vol. 41, no. 1, pp. 72–78, 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. K. G. D. Tharangie, C. M. A. Irfan, K. Yamad, and A. Marasinghe, “Kansei colour concepts to improve effective colour selection in designing human computer interfaces,” International Journal of Computer Science Issues (IJCSI), vol. 7, no. 3, article 5, 2010. View at Google Scholar
  16. T. Wellings, M. Williams, and C. Tennant, “Understanding customers' holistic perception of switches in automotive human-machine interfaces,” Applied Ergonomics, vol. 41, no. 1, pp. 8–17, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. J. L. Nevins, D. E. Whitney, and T. L. De Fazio, Concurrent Design of Products and Processes: A Strategy for the Next Generation in Manufacturing, McGraw-Hill, New York, NY, USA, 1989.
  18. G. Pahl, W. Beitz, J. Feldhusen, and K.-H. Grote, Engineering Design: A Systematic Approach, Springer, London, UK, 3rd edition, 2007.
  19. N. Cross, Engineering Design Methods: Strategies for Product Design, John Wiley & Sons, Chichester, UK, 3rd edition, 2000.
  20. J.-R. Chou, “A Kansei evaluation approach based on the technique of computing with words,” Advanced Engineering Informatics, vol. 30, no. 1, pp. 1–15, 2016. View at Publisher · View at Google Scholar · View at Scopus
  21. H. Liao, Z. Xu, X.-J. Zeng, and D.-L. Xu, “An enhanced consensus reaching process in group decision making with intuitionistic fuzzy preference relations,” Information Sciences, vol. 329, pp. 274–286, 2016. View at Publisher · View at Google Scholar · View at Scopus
  22. F. M. Mata, J. Carlos, and R. Rodríguez, A Web-Based Consensus Support System Dealing with Heterogeneous Information, vol. 267, Springer, Berlin, Germany, 2011.
  23. T. González-Arteaga, J. C. R. Alcantud, and R. de Andrés Calle, “A new consensus ranking approach for correlated ordinal information based on Mahalanobis distance,” Information Sciences, vol. 372, pp. 546–564, 2016. View at Publisher · View at Google Scholar · View at Scopus
  24. J. Kacprzyk and M. Fedrizzi, “A 'soft' measure of consensus in the setting of partial (fuzzy) preferences,” European Journal of Operational Research, vol. 34, no. 3, pp. 316–325, 1988. View at Publisher · View at Google Scholar · View at Scopus
  25. B. Zhang, Y. Dong, and Y. Xu, “Multiple attribute consensus rules with minimum adjustments to support consensus reaching,” Knowledge-Based Systems, vol. 67, pp. 35–48, 2014. View at Publisher · View at Google Scholar · View at Scopus
  26. J. E. Kennedy and C. Russell, Swarm Intelligence, Academic Press, San Diego, Calif, USA, 2001.
  27. H. Shi Y and R. C. Eberhart, “Parameter selection in particle swarm optimization,” in Proceedings of the 7th International Conference on Evolutionary Programming (EP '98), pp. 591–600, Springer, San Diego, Calif, USA, 1998.
  28. T. L. Saaty, The Analytic Hierarchy Process: Planning, Priority Setting, McGraw-Hill International Book, New York, NY, USA, 1980. View at MathSciNet
  29. R. Eberhart and J. Kennedy, “A new optimizer using particle swarm theory,” in Proceedings of the Sixth International Symposium on Micro Machine and Human Science (MHS '95), 1995.