Group Decision and Negotiation

, Volume 22, Issue 2, pp 189–205 | Cite as

PROMETHEE Group Decision Support System and the House of Quality

  • Majid Behzadian
  • Seyyed-Mahdi Hosseini-Motlagh
  • Joshua Ignatius
  • Mark Goh
  • Mohammad Mehdi Sepehri


Quality function deployment (QFD) is a multi-step method that monitors customer needs throughout a product development process. The House of Quality (HOQ) exercise undertaken in the first phase of QFD is considered as the most important, since customer needs must be accurately translated into a set of technical requirements for the final product. This paper provides a PROMETHEE group decision support system (GDSS) approach that integrates the design preferences of the QFD team. We highlight the selection and ranking of the technical requirements in the HOQ exercise, where a group of multidisciplinary decision makers (DMs) in a globally dispersed QFD team is required to input their individual preferences. Our approach advances the HOQ group decision making context in three important areas. First, it treats each criterion and DM as unique in terms of the preference function and threshold levels. Second, it seeks a multi-criteria approach for the HOQ process, where some DMs may play a more important role than others on a certain criterion. Third, sensitivity analysis through the Geometrical Analysis for Interactive Assistance (GAIA) plane provides valuable information about the conflicts, similarities, or independencies between the criterion and the DMs, respectively. A case on an automotive part illustrates the performance of the PROMOTHEE approach with GAIA.




Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Armacost RL, Componation PJ, Mullens MA, Swart WW (1994) An AHP framework for prioritizing customer requirements in QFD: an industrialized housing application. IIE Trans 26(4): 72–79CrossRefGoogle Scholar
  2. Bae SM, Ha SH, Park SC (2005) A web-based system for analyzing the voices of call center customers in the service industry. Expert Syst Appl 28: 29–41CrossRefGoogle Scholar
  3. Bai H, Kwong K (2003) Inexact genetic algorithm approach to target values setting of engineering requirements in QFD. Int J Prod Res 41(16): 3861–3881CrossRefGoogle Scholar
  4. Behzadian M, Kazemzadeh RB, Albadvi A, Aghdasi M (2010) PROMETHEE: a comprehensive literature review on applications and methodologies. Eur J Oper Res 200: 198–215CrossRefGoogle Scholar
  5. Benner M, Linnemann AR, Jongen WMF, Folstar P (2003) Quality function deployment (QFD)—can it be used to develop food products. Food Qual Prefer 14: 327–339CrossRefGoogle Scholar
  6. Brans JP (1982) Lingenierie de la decision. Elaboration dinstruments daide a la decision. Methode PROMETHEE. In: Nadeau R, LandryM(eds) Laide a la decision: nature, instrument s et perspectives davenir. Presses de Universite Laval, QuebecGoogle Scholar
  7. Brans JP, Vincke P (1985) A preference ranking organization method: the PROMETHEE method for MCDM. Manag Sci 31: 641–656CrossRefGoogle Scholar
  8. Brans JP, Mareschal B (2005) PROMETHEE methods. In: Figueira J, Greco S, Ehrgott M (eds) Multiple criteria decision analysis: state of the art surveys. Springer, BerlinGoogle Scholar
  9. Buyukozkan G, Feyzioglu O (2005) Group decision-making to better respond to customer needs in software development. Comput Ind Eng 48(2): 427–441CrossRefGoogle Scholar
  10. Buyukozkan G, Feyzioglu O, Rual D (2007) Fuzzy group decision-making to multiple preference formats in quality function deployment. Comput Ind 58(5): 392–402CrossRefGoogle Scholar
  11. Carlsson C, Walden P (1995) AHP in political group decision: a study in the art of possibilities. Interfaces 25(4): 14–29CrossRefGoogle Scholar
  12. Chan LK, Wu ML (2005) A systematic approach to quality function deployment with a full illustrative example. Omega 33: 119–139CrossRefGoogle Scholar
  13. Chen Y, Chen L (2006) A non-linear possibilistic regression approach to model functional relationships in product planning. Int J Adv Manuf Technol 28: 1175–1181CrossRefGoogle Scholar
  14. Cohen L (1995) Quality function deployment: how to make it work for you. Addison-Wesley, ReadingGoogle Scholar
  15. Colson G (2000) The OR’s prize winner and the software ARGOS: how a multijudge and multicriteria ranking GDSS helps a jury to attribute a scientific award. Comput Oper Res 27: 741–755CrossRefGoogle Scholar
  16. Cristiano JJ, Liker JK, White CC (2000) Customer-driven product development through quality function deployment in the US and Japan. J Prod Innov Manag 17(4): 286–308CrossRefGoogle Scholar
  17. Dweiri FT, Kablan MM (2005) An integration of the analytic hierarchy process into the quality function deployment process. Int J Ind Eng Theory Appl Pract 12(2): 180–188Google Scholar
  18. Fung RYK, Chen YZ, Chen L, Tang JF (2005) A fuzzy expected value-based goal programming model for product planning using quality function deployment. Eng Optim 37(6): 633–647CrossRefGoogle Scholar
  19. Haralambopoulos DA, Polatidis H (2003) Renewable energy projects: structuring a multicriteria group decision-making framework. Renew Energy 28: 961–973CrossRefGoogle Scholar
  20. Ho ESSA, Lai YJ, Chang SI (1999) An integrated group decision-making approach to quality function deployment. IIE Trans 31(6): 553–567CrossRefGoogle Scholar
  21. Hsiao SW (2002) Concurrent design method for developing a new product. Int J Ind Ergon 29: 41–55CrossRefGoogle Scholar
  22. Hsiao SW, Liu E (2005) A structural component-based approach for designing product family. Comput Ind 56: 13–28CrossRefGoogle Scholar
  23. Ignatius J, Motlagh SMH, Motlagh MM, Behzadian M, Mustafa A (2010) Hybrid models in decision making under uncertainty: the case of training provider evaluation. J Intell Fuzzy Syst 21: 147–162Google Scholar
  24. Jariri F, Zegordi SH (2008) Quality function deployment planning for platform design. Int J Adv Manuf Technol 36: 419–430CrossRefGoogle Scholar
  25. Kahraman C, Ertay T, Büyüközkan G (2006) A fuzzy optimization model for QFD planning process using analytic network approach. Eur J Oper Res 171: 390–411CrossRefGoogle Scholar
  26. Karsak EE (2004) Fuzzy multiple objective decision-making approach to prioritize design requirements in quality function deployment. Int J Prod Res 42(18): 3957–3974CrossRefGoogle Scholar
  27. Kazemzadeh RB, Behzadian M, Aghdasi M, Albadvi A (2009) Integration of marketing research techniques into house of quality and product family design. Int J Adv Manuf Technol 41: 1019–1033CrossRefGoogle Scholar
  28. Kim KJ, Moskowitz H, Dhingra A, Evans G (2000) Fuzzy multicriteria models for quality function deployment. Eur J Oper Res 121(3): 504–518CrossRefGoogle Scholar
  29. Lai X, Xie M, Tan KC (2005) Dynamic programming for QFD optimization. Qual Reliab Eng Int 21(8): 769–780CrossRefGoogle Scholar
  30. Liu ST (2005) Rating design requirements in fuzzy quality function deployment via a mathematical programming approach. Int J Prod Res 43(3): 497–513CrossRefGoogle Scholar
  31. Macharis C, Brans JP, Mareschal B (1998) The GDSS PROMETHEE procedure—a PROMETHEE-GAIA based procedure for group decision support. J Decis Syst 7: 283–307Google Scholar
  32. Mareschal B, Brans JP (1988) Geometrical representations for MCDA: the GAIA module. Eur J Oper Res 34(1): 69–77CrossRefGoogle Scholar
  33. Morais DC, De Almeida AT (2007) Group decision-making for leakage management strategy of water network, resources. Conserv Recycl 52(2): 441–459CrossRefGoogle Scholar
  34. Perez J (1995) Comments on Saaty’s AHP. Manag Sci 41(6): 1091–1095CrossRefGoogle Scholar
  35. Raharjo H, Xie M, Brombacher AC (2006) Prioritizing quality characteristics in dynamic quality function deployment. Int J Prod Res 44(23): 5005–5018CrossRefGoogle Scholar
  36. Raju KS, Duckstein L, Arondel C (2000) Multicriterion analysis for sustainable water resources planning: a case study in Spain. Water Resour Manag 14: 435–456CrossRefGoogle Scholar
  37. Reich Y, Levy E (2004) Managing product design quality under resource constraints. Int J Prod Res 42(13): 2555–2572CrossRefGoogle Scholar
  38. Shen XX, Tan KC, Xie M (2000) An integrated approach to innovative product development using Kano’s model and QFD. Eur J Innov Manag 3(2): 91–99CrossRefGoogle Scholar
  39. Temponi C, Yen J, Tiao WA (1999) House of quality: a fuzzy logic-based requirements analysis. Eur J Oper Res 117: 340–354CrossRefGoogle Scholar
  40. Tu YL, Fung RYK, Tang JF, Kam JJ (2003) Computer aided customer interface for rapid product development. Int J Adv Manuf Technol 21(10–11): 743–753CrossRefGoogle Scholar
  41. Xie M, Tan KC, Goh TN (2003) Advanced QFD application. ASQ Quality Press, MilwaukeeGoogle Scholar
  42. Zakarian A, Kusiak A (1999) Forming teams: an analytical approach. IIE Trans 31: 85–97Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Majid Behzadian
    • 1
  • Seyyed-Mahdi Hosseini-Motlagh
    • 2
  • Joshua Ignatius
    • 3
  • Mark Goh
    • 4
  • Mohammad Mehdi Sepehri
    • 5
  1. 1.Department of Industrial EngineeringShomal UniversityAmolIran
  2. 2.Department of Industrial EngineeringIran University of Science and TechnologyTehranIran
  3. 3.School of Mathematical SciencesUniversiti Sains MalaysiaPenangMalaysia
  4. 4.School of ManagementUniversity of South AustraliaAdelaideAustralia
  5. 5.Department of Industrial EngineeringTarbiat Modares UniversityTehranIran

Personalised recommendations