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Combining quality function deployment with simple additive weighting for interval-valued fuzzy multi-criteria decision-making with dependent evaluation criteria

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Abstract

In the past, lots of multi-criteria decision-making (MCDM) methods included simple additive weighting (SAW) extended under fuzzy environment into multi-criteria decision-making (FMCDM) methods to encompass uncertainty and vagueness of data. The extensions were first used in FMCDM with independent evaluation criteria, and then, FMCDM could be associated with quality function deployment (QFD) to break the tie of dependent evaluation criteria. Commonly, alternative ratings and criteria weights in FMCDM were expressed by general fuzzy numbers (i.e., triangular or trapezoidal fuzzy numbers). Recently, some approaches proposed FMCDM with independent evaluation criteria under interval-valued fuzzy environment. For interval-valued fuzzy numbers, FMCDM with dependent evaluation criteria was scarcely elaborated due to computation complexity. Besides, QFD was also generalized under some fuzzy environments consisting of triangular fuzzy numbers or trapezoidal fuzzy numbers, but not interval-valued fuzzy environment. Practically, interval-valued fuzzy numbers are deemed as a kind of fuzzy number that can grasp more information than other fuzzy numbers, but the kind of fuzzy number is more complex on computation than others. Based on above, we desire to extend QFD and SAW under interval-valued fuzzy environment for FMCDM with dependent evaluation criteria. By a rational technique of combining QFD with SAW under fuzzy environment, the computation tie of interval-valued fuzzy numbers corresponding to dependent evaluation criteria is resolved, and more messages are grasped than using other fuzzy numbers in FMCDM.

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References

  • Ashtiani A, Haghighirad F, Makui A, Montazer GA (2009) Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets. Appl Soft Comput 9:457–461

    Google Scholar 

  • Bellman RE, Zadeh LA (1970) Decision-making in a fuzzy environment. Manag Sci 17:141–164

    MathSciNet  MATH  Google Scholar 

  • Chan LK, Wu ML (2002) Quality function deployment: a literature review. Eur J Oper Res 143:463–497

    MATH  Google Scholar 

  • Chen CT (2000) Extensions to the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114:1–9

    MATH  Google Scholar 

  • Chen TY (2011) Interval-valued fuzzy TOPSIS method with leniency reduction and an experimental analysis. Expert Syst Appl 11:4591–4608

    Google Scholar 

  • Chen SJ, Hwang CL (1992) Fuzzy multiple attribute decision making: methods and applications. Springer, New York

    MATH  Google Scholar 

  • Chen LH, Ko WC (2009) Fuzzy approaches to quality function deployment for new product design. Fuzzy Sets Syst 160:2620–2639

    MathSciNet  MATH  Google Scholar 

  • Churchman CW, Ackoff RJ, Amoff EL (1957) Introduction to operation research. Wiley, New York

    Google Scholar 

  • Delgado M, Verdegay JL, Vila MA (1992) Linguistic decision-making models. Int J Intell Syst 7:479–492

    MATH  Google Scholar 

  • Epp SS (1990) Discrete mathematics with applications. Wadsworth, Belmont

    MATH  Google Scholar 

  • Fan ZP, Ma J, Zhang Q (2002) An approach to multiple attribute decision making based on fuzzy preference information on alternatives. Fuzzy Sets Syst 131:101–106

    MathSciNet  MATH  Google Scholar 

  • Gorzalczany MB (1987) A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Syst 21:1–17

    MathSciNet  MATH  Google Scholar 

  • Herrera F, Herrera-Viedma E, Verdegay JL (1996) A model of consensus in group decision making under linguistic assessments. Fuzzy Sets Syst 78:73–87

    MathSciNet  MATH  Google Scholar 

  • Hwang CL, Yoon K (1981) Multiple attribute decision making: methods and applications. Springer, New York

    MATH  Google Scholar 

  • Jain R (1978) A procedure for multi-aspect decision making using fuzzy sets. Int J Syst Sci 8:1–7

    MATH  Google Scholar 

  • Joshi D, Kumar S (2016) Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making. Eur J Oper Res 248:183–191

    MathSciNet  MATH  Google Scholar 

  • Kacprzyk J, Fedrizzi M, Nurmi H (1992) Group decision making and consensus under fuzzy preferences and fuzzy majority. Fuzzy Sets Syst 49:21–31

    MathSciNet  MATH  Google Scholar 

  • Keeney R, Raiffa H (1976) Decision with multiple objective: preference and value tradeoffs. Wiley, New Work

    Google Scholar 

  • Kuo MS, Liang GS (2012) A soft computing method of performance evaluation with MCDM based on interval-valued fuzzy numbers. Appl Soft Comput 12:476–485

    Google Scholar 

  • Kuo TC, Wu HH, Shieh JI (2009) Integration of environmental considerations in quality function deployment by using fuzzy logic. Expert Syst Appl 36:7148–7156

    Google Scholar 

  • Lee HS (2005a) A fuzzy multi-criteria decision making model for the selection of the distribution center. Lect Notes Artif Intell 3612:1290–1299

    Google Scholar 

  • Lee HS (2005b) On fuzzy preference relation in group decision making. Int J Comput Math 82:133–140

    MathSciNet  MATH  Google Scholar 

  • Lee CS, Chung CC, Lee HS, Gan GY, Chou MT (2016) An interval-valued fuzzy number approach for supplier selection. J Mar Sci Tech-Taiw 24:384–389

    Google Scholar 

  • Li RJ (1999) Fuzzy method in group decision making. Comput Math Appl 38:91–101

    MathSciNet  MATH  Google Scholar 

  • Liang GS (1999) Fuzzy MCDM based on ideal and anti-ideal concepts. Eur J Oper Res 112:682–691

    MATH  Google Scholar 

  • Liang GS (2010) Applying fuzzy quality function deployment to identify service management requirements. Qual Quant 44:47–57

    Google Scholar 

  • Liang GS, Wang MJ (1991) A fuzzy multi-criteria decision-making method for facility site selection. Int J Prod Res 29:2313–2330

    MATH  Google Scholar 

  • Lin LZ, Chen WC, Chang TJ (2011) Using FQFD to analyze island accommodation management in fuzzy linguistic preferences. Expert Syst Appl 38:7738–7745

    Google Scholar 

  • Lin LZ, Yeh HR, Wang MC (2015) Integration of Kano’s model into FQFD for Taiwanese Ban-Doh banquet culture. Tour Manag 46:245–262

    Google Scholar 

  • Liu F, Zhang WG, Fu JH (2012) A new method of obtaining the priority weights from an interval fuzzy preference relation. Inf Sci 185:32–42

    MATH  Google Scholar 

  • Lowe A, Ridgway K, Atkinson H (2000) QFD in new production technology evaluation. Int J Prod Econ 67:103–112

    Google Scholar 

  • Matook S, Indulska M (2009) Improving the quality of process reference models: a quality function deployment-based approach. Decis Support Syst 47:60–71

    Google Scholar 

  • Modarres M, Sadi-Nezhad S (2005) Fuzzy simple additive weighting method by preference ratio. Intell Autom Soft Co 11:235–244

    Google Scholar 

  • Mokhtarian MN (2015) A note on “Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets”. Appl Soft Comput 26:513–514

    Google Scholar 

  • Nakamura K (1986) Preference relations on a set of fuzzy utilities as a basis for decision making. Fuzzy Sets Syst 20:147–162

    MathSciNet  MATH  Google Scholar 

  • Partovi FY, Corredoira RA (2002) Quality function deployment for the good of soccer. Eur J Oper Res 137:642–656

    MATH  Google Scholar 

  • Raj PA, Kumar DN (1999) Ranking alternatives with fuzzy weights using maximizing set and minimizing set. Fuzzy Sets Syst 105:365–375

    MATH  Google Scholar 

  • Rashid T, Beg I, Husnine SM (2014) Robot selection by using generalized interval-valued fuzzy numbers with TOPSIS. Appl Soft Comput 21:462–468

    Google Scholar 

  • Tanino T (1984) Fuzzy preference in group decision making. Fuzzy Sets Syst 12:117–131

    MathSciNet  MATH  Google Scholar 

  • Vahdani B, Tavakkoli-Moghaddam R, Mousavi SM, Ghodratnama A (2013) Soft computing based on new interval-valued fuzzy modified multi-criteria decision-making method. Appl Soft Comput 13:165–172

    Google Scholar 

  • Wang YJ (2014) A criteria weighting approach by combining fuzzy quality function deployment with relative preference relation. Appl Soft Comput 14:419–430

    Google Scholar 

  • Wang YJ (2015) A fuzzy multi-criteria decision-making model based on simple additive weighting method and relative preference relation. Appl Soft Comput 30:412–420

    Google Scholar 

  • Wang YJ (2016) Applying FQFD and utility representative functions under fuzzy environment for FMCDM. J Test Eval 44:1776–1790

    Google Scholar 

  • Wang CY, Chen SM (2017) Multiple attribute decision making based on interval-valued intuitionistic fuzzy sets, linear programming methodology, and the extended TOPSIS method. Inf Sci 397–398:155–167

    Google Scholar 

  • Yao JS, Lin FT (2002) Constructing a fuzzy flow-shop sequencing model based on statistical data. Int J Approx Reason 29:215–234

    MathSciNet  MATH  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353

    MATH  Google Scholar 

Download references

Acknowledgements

This research work was partially supported by the Ministry of Science and Technology of the Republic of China under Grant No. MOST 106-2410-H-346-002.

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  1. Department of Shipping and Transportation Management, National Penghu University of Science and Technology, Magong, 880, Penghu, Taiwan, Republic of China

    Yu-Jie Wang

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Wang, YJ. Combining quality function deployment with simple additive weighting for interval-valued fuzzy multi-criteria decision-making with dependent evaluation criteria. Soft Comput 24, 7757–7767 (2020). https://doi.org/10.1007/s00500-019-04394-5

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